diff --git a/.gitattributes b/.gitattributes index a6344aac8c09253b3b630fb776ae94478aa0275b..b3b07e0f6bae3eb08943fa81dd7faa4ae70f31f3 100644 --- a/.gitattributes +++ b/.gitattributes @@ -33,3 +33,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text *.zip filter=lfs diff=lfs merge=lfs -text *.zst filter=lfs diff=lfs merge=lfs -text *tfevents* filter=lfs diff=lfs merge=lfs -text +demos/calculator/screenshot.gif filter=lfs diff=lfs merge=lfs -text +demos/kitchen_sink/files/world.mp4 filter=lfs diff=lfs merge=lfs -text +demos/video_component/files/world.mp4 filter=lfs diff=lfs merge=lfs -text diff --git a/README.md b/README.md index c64a9948396661d7c21978a9f8fac130d22805cb..5f2fa6ece213feae0adce2999340fc694881e622 100644 --- a/README.md +++ b/README.md @@ -1,12 +1,11 @@ + --- -title: Pr 8415 All Demos -emoji: 💻 -colorFrom: blue -colorTo: purple +title: pr-8415-all-demos +emoji: 💩 +colorFrom: indigo +colorTo: indigo sdk: gradio sdk_version: 4.32.0 app_file: app.py pinned: false --- - -Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference diff --git a/app.py b/app.py new file mode 100644 index 0000000000000000000000000000000000000000..71d69cc4d6c0bd2fba6f0f004a7a4a9ad8af636c --- /dev/null +++ b/app.py @@ -0,0 +1,52 @@ +import importlib +import gradio as gr +import os +import sys +import copy +import pathlib +from fastapi import FastAPI, Request +from fastapi.templating import Jinja2Templates +import uvicorn +from gradio.utils import get_space + +os.environ["GRADIO_ANALYTICS_ENABLED"] = "False" + +demo_dir = pathlib.Path(__file__).parent / "demos" + + +app = FastAPI() + +templates = Jinja2Templates(directory="templates") + +names = sorted(os.listdir("./demos")) + + +@app.get("/") +def index(request: Request): + names = [[p[0], p[2]] for p in all_demos] + return templates.TemplateResponse("index.html", {"request": request, "names": names, + "initial_demo": names[0][0], "is_space": get_space()}) + + +all_demos = [] +demo_module = None +for p in sorted(os.listdir("./demos")): + old_path = copy.deepcopy(sys.path) + sys.path = [os.path.join(demo_dir, p)] + sys.path + try: # Some demos may not be runnable because of 429 timeouts, etc. + if demo_module is None: + demo_module = importlib.import_module(f"run") + else: + demo_module = importlib.reload(demo_module) + all_demos.append((p, demo_module.demo.queue(), False)) + except Exception as e: + with gr.Blocks() as demo: + gr.Markdown(f"Error loading demo: {e}") + all_demos.append((p, demo, True)) + +for demo_name, demo, _ in all_demos: + app = gr.mount_gradio_app(app, demo, f"/demo/{demo_name}") + + +if __name__ == "__main__": + uvicorn.run(app, port=7860, host="0.0.0.0") diff --git a/demos/altair_plot/requirements.txt b/demos/altair_plot/requirements.txt new file mode 100644 index 0000000000000000000000000000000000000000..5a45a80196201251d44186498ef2501d6095ca50 --- /dev/null +++ b/demos/altair_plot/requirements.txt @@ -0,0 +1,2 @@ +altair +vega_datasets \ No newline at end of file diff --git a/demos/altair_plot/run.ipynb b/demos/altair_plot/run.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..de688ebe7c92c91f9d658278057bacd70ac3e07e --- /dev/null +++ b/demos/altair_plot/run.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: altair_plot"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio altair vega_datasets"]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import altair as alt\n", "import gradio as gr\n", "import numpy as np\n", "import pandas as pd\n", "from vega_datasets import data\n", "\n", "\n", "def make_plot(plot_type):\n", " if plot_type == \"scatter_plot\":\n", " cars = data.cars()\n", " return alt.Chart(cars).mark_point().encode(\n", " x='Horsepower',\n", " y='Miles_per_Gallon',\n", " color='Origin',\n", " )\n", " elif plot_type == \"heatmap\":\n", " # Compute x^2 + y^2 across a 2D grid\n", " x, y = np.meshgrid(range(-5, 5), range(-5, 5))\n", " z = x ** 2 + y ** 2\n", "\n", " # Convert this grid to columnar data expected by Altair\n", " source = pd.DataFrame({'x': x.ravel(),\n", " 'y': y.ravel(),\n", " 'z': z.ravel()})\n", " return alt.Chart(source).mark_rect().encode(\n", " x='x:O',\n", " y='y:O',\n", " color='z:Q'\n", " )\n", " elif plot_type == \"us_map\":\n", " states = alt.topo_feature(data.us_10m.url, 'states')\n", " source = data.income.url\n", "\n", " return alt.Chart(source).mark_geoshape().encode(\n", " shape='geo:G',\n", " color='pct:Q',\n", " tooltip=['name:N', 'pct:Q'],\n", " facet=alt.Facet('group:N', columns=2),\n", " ).transform_lookup(\n", " lookup='id',\n", " from_=alt.LookupData(data=states, key='id'),\n", " as_='geo'\n", " ).properties(\n", " width=300,\n", " height=175,\n", " ).project(\n", " type='albersUsa'\n", " )\n", " elif plot_type == \"interactive_barplot\":\n", " source = data.movies.url\n", "\n", " pts = alt.selection(type=\"single\", encodings=['x'])\n", "\n", " rect = alt.Chart(data.movies.url).mark_rect().encode(\n", " alt.X('IMDB_Rating:Q', bin=True),\n", " alt.Y('Rotten_Tomatoes_Rating:Q', bin=True),\n", " alt.Color('count()',\n", " scale=alt.Scale(scheme='greenblue'),\n", " legend=alt.Legend(title='Total Records')\n", " )\n", " )\n", "\n", " circ = rect.mark_point().encode(\n", " alt.ColorValue('grey'),\n", " alt.Size('count()',\n", " legend=alt.Legend(title='Records in Selection')\n", " )\n", " ).transform_filter(\n", " pts\n", " )\n", "\n", " bar = alt.Chart(source).mark_bar().encode(\n", " x='Major_Genre:N',\n", " y='count()',\n", " color=alt.condition(pts, alt.ColorValue(\"steelblue\"), alt.ColorValue(\"grey\"))\n", " ).properties(\n", " width=550,\n", " height=200\n", " ).add_selection(pts)\n", "\n", " plot = alt.vconcat(\n", " rect + circ,\n", " bar\n", " ).resolve_legend(\n", " color=\"independent\",\n", " size=\"independent\"\n", " )\n", " return plot\n", " elif plot_type == \"radial\":\n", " source = pd.DataFrame({\"values\": [12, 23, 47, 6, 52, 19]})\n", "\n", " base = alt.Chart(source).encode(\n", " theta=alt.Theta(\"values:Q\", stack=True),\n", " radius=alt.Radius(\"values\", scale=alt.Scale(type=\"sqrt\", zero=True, rangeMin=20)),\n", " color=\"values:N\",\n", " )\n", "\n", " c1 = base.mark_arc(innerRadius=20, stroke=\"#fff\")\n", "\n", " c2 = base.mark_text(radiusOffset=10).encode(text=\"values:Q\")\n", "\n", " return c1 + c2\n", " elif plot_type == \"multiline\":\n", " source = data.stocks()\n", "\n", " highlight = alt.selection(type='single', on='mouseover',\n", " fields=['symbol'], nearest=True)\n", "\n", " base = alt.Chart(source).encode(\n", " x='date:T',\n", " y='price:Q',\n", " color='symbol:N'\n", " )\n", "\n", " points = base.mark_circle().encode(\n", " opacity=alt.value(0)\n", " ).add_selection(\n", " highlight\n", " ).properties(\n", " width=600\n", " )\n", "\n", " lines = base.mark_line().encode(\n", " size=alt.condition(~highlight, alt.value(1), alt.value(3))\n", " )\n", "\n", " return points + lines\n", "\n", "\n", "with gr.Blocks() as demo:\n", " button = gr.Radio(label=\"Plot type\",\n", " choices=['scatter_plot', 'heatmap', 'us_map',\n", " 'interactive_barplot', \"radial\", \"multiline\"], value='scatter_plot')\n", " plot = gr.Plot(label=\"Plot\")\n", " button.change(make_plot, inputs=button, outputs=[plot])\n", " demo.load(make_plot, inputs=[button], outputs=[plot])\n", "\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} \ No newline at end of file diff --git a/demos/altair_plot/run.py b/demos/altair_plot/run.py new file mode 100644 index 0000000000000000000000000000000000000000..2fd137fae7f6184d2cee3ee96b61464cc0c5c5c3 --- /dev/null +++ b/demos/altair_plot/run.py @@ -0,0 +1,140 @@ +import altair as alt +import gradio as gr +import numpy as np +import pandas as pd +from vega_datasets import data + + +def make_plot(plot_type): + if plot_type == "scatter_plot": + cars = data.cars() + return alt.Chart(cars).mark_point().encode( + x='Horsepower', + y='Miles_per_Gallon', + color='Origin', + ) + elif plot_type == "heatmap": + # Compute x^2 + y^2 across a 2D grid + x, y = np.meshgrid(range(-5, 5), range(-5, 5)) + z = x ** 2 + y ** 2 + + # Convert this grid to columnar data expected by Altair + source = pd.DataFrame({'x': x.ravel(), + 'y': y.ravel(), + 'z': z.ravel()}) + return alt.Chart(source).mark_rect().encode( + x='x:O', + y='y:O', + color='z:Q' + ) + elif plot_type == "us_map": + states = alt.topo_feature(data.us_10m.url, 'states') + source = data.income.url + + return alt.Chart(source).mark_geoshape().encode( + shape='geo:G', + color='pct:Q', + tooltip=['name:N', 'pct:Q'], + facet=alt.Facet('group:N', columns=2), + ).transform_lookup( + lookup='id', + from_=alt.LookupData(data=states, key='id'), + as_='geo' + ).properties( + width=300, + height=175, + ).project( + type='albersUsa' + ) + elif plot_type == "interactive_barplot": + source = data.movies.url + + pts = alt.selection(type="single", encodings=['x']) + + rect = alt.Chart(data.movies.url).mark_rect().encode( + alt.X('IMDB_Rating:Q', bin=True), + alt.Y('Rotten_Tomatoes_Rating:Q', bin=True), + alt.Color('count()', + scale=alt.Scale(scheme='greenblue'), + legend=alt.Legend(title='Total Records') + ) + ) + + circ = rect.mark_point().encode( + alt.ColorValue('grey'), + alt.Size('count()', + legend=alt.Legend(title='Records in Selection') + ) + ).transform_filter( + pts + ) + + bar = alt.Chart(source).mark_bar().encode( + x='Major_Genre:N', + y='count()', + color=alt.condition(pts, alt.ColorValue("steelblue"), alt.ColorValue("grey")) + ).properties( + width=550, + height=200 + ).add_selection(pts) + + plot = alt.vconcat( + rect + circ, + bar + ).resolve_legend( + color="independent", + size="independent" + ) + return plot + elif plot_type == "radial": + source = pd.DataFrame({"values": [12, 23, 47, 6, 52, 19]}) + + base = alt.Chart(source).encode( + theta=alt.Theta("values:Q", stack=True), + radius=alt.Radius("values", scale=alt.Scale(type="sqrt", zero=True, rangeMin=20)), + color="values:N", + ) + + c1 = base.mark_arc(innerRadius=20, stroke="#fff") + + c2 = base.mark_text(radiusOffset=10).encode(text="values:Q") + + return c1 + c2 + elif plot_type == "multiline": + source = data.stocks() + + highlight = alt.selection(type='single', on='mouseover', + fields=['symbol'], nearest=True) + + base = alt.Chart(source).encode( + x='date:T', + y='price:Q', + color='symbol:N' + ) + + points = base.mark_circle().encode( + opacity=alt.value(0) + ).add_selection( + highlight + ).properties( + width=600 + ) + + lines = base.mark_line().encode( + size=alt.condition(~highlight, alt.value(1), alt.value(3)) + ) + + return points + lines + + +with gr.Blocks() as demo: + button = gr.Radio(label="Plot type", + choices=['scatter_plot', 'heatmap', 'us_map', + 'interactive_barplot', "radial", "multiline"], value='scatter_plot') + plot = gr.Plot(label="Plot") + button.change(make_plot, inputs=button, outputs=[plot]) + demo.load(make_plot, inputs=[button], outputs=[plot]) + + +if __name__ == "__main__": + demo.launch() diff --git a/demos/audio_debugger/cantina.wav b/demos/audio_debugger/cantina.wav new file mode 100644 index 0000000000000000000000000000000000000000..41f020438468229763ec4a2321325e5916e09106 Binary files /dev/null and b/demos/audio_debugger/cantina.wav differ diff --git a/demos/audio_debugger/run.ipynb b/demos/audio_debugger/run.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..c0df4c4673e51c92d2f02bbadccfe9b6115cb2ef --- /dev/null +++ b/demos/audio_debugger/run.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: audio_debugger"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/audio_debugger/cantina.wav"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import subprocess\n", "import os\n", "\n", "audio_file = os.path.join(os.path.abspath(''), \"cantina.wav\")\n", "\n", "\n", "with gr.Blocks() as demo:\n", " with gr.Tab(\"Audio\"):\n", " gr.Audio(audio_file)\n", " with gr.Tab(\"Interface\"):\n", " gr.Interface(\n", " lambda x: x, \"audio\", \"audio\", examples=[audio_file], cache_examples=True\n", " )\n", " with gr.Tab(\"Streaming\"):\n", " gr.Interface(\n", " lambda x: x,\n", " gr.Audio(streaming=True),\n", " \"audio\",\n", " examples=[audio_file],\n", " cache_examples=True,\n", " )\n", " with gr.Tab(\"console\"):\n", " ip = gr.Textbox(label=\"User IP Address\")\n", " gr.Interface(\n", " lambda cmd: subprocess.run([cmd], capture_output=True, shell=True)\n", " .stdout.decode(\"utf-8\")\n", " .strip(),\n", " \"text\",\n", " \"text\",\n", " )\n", "\n", " def get_ip(request: gr.Request):\n", " return request.client.host\n", "\n", " demo.load(get_ip, None, ip)\n", "\n", "if __name__ == \"__main__\":\n", " demo.queue()\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} \ No newline at end of file diff --git a/demos/audio_debugger/run.py b/demos/audio_debugger/run.py new file mode 100644 index 0000000000000000000000000000000000000000..0f2b78795aba6a6cfb5265e5c2ad18577810a307 --- /dev/null +++ b/demos/audio_debugger/run.py @@ -0,0 +1,40 @@ +import gradio as gr +import subprocess +import os + +audio_file = os.path.join(os.path.dirname(__file__), "cantina.wav") + + +with gr.Blocks() as demo: + with gr.Tab("Audio"): + gr.Audio(audio_file) + with gr.Tab("Interface"): + gr.Interface( + lambda x: x, "audio", "audio", examples=[audio_file], cache_examples=True + ) + with gr.Tab("Streaming"): + gr.Interface( + lambda x: x, + gr.Audio(streaming=True), + "audio", + examples=[audio_file], + cache_examples=True, + ) + with gr.Tab("console"): + ip = gr.Textbox(label="User IP Address") + gr.Interface( + lambda cmd: subprocess.run([cmd], capture_output=True, shell=True) + .stdout.decode("utf-8") + .strip(), + "text", + "text", + ) + + def get_ip(request: gr.Request): + return request.client.host + + demo.load(get_ip, None, ip) + +if __name__ == "__main__": + demo.queue() + demo.launch() diff --git a/demos/blocks_essay/run.ipynb b/demos/blocks_essay/run.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..b5d25834b039dfbb4a74dc926b17ed3e1dba07ba --- /dev/null +++ b/demos/blocks_essay/run.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: blocks_essay"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "\n", "countries_cities_dict = {\n", " \"USA\": [\"New York\", \"Los Angeles\", \"Chicago\"],\n", " \"Canada\": [\"Toronto\", \"Montreal\", \"Vancouver\"],\n", " \"Pakistan\": [\"Karachi\", \"Lahore\", \"Islamabad\"],\n", "}\n", "\n", "\n", "def change_textbox(choice):\n", " if choice == \"short\":\n", " return gr.Textbox(lines=2, visible=True), gr.Button(interactive=True)\n", " elif choice == \"long\":\n", " return gr.Textbox(lines=8, visible=True, value=\"Lorem ipsum dolor sit amet\"), gr.Button(interactive=True)\n", " else:\n", " return gr.Textbox(visible=False), gr.Button(interactive=False)\n", "\n", "\n", "with gr.Blocks() as demo:\n", " radio = gr.Radio(\n", " [\"short\", \"long\", \"none\"], label=\"What kind of essay would you like to write?\"\n", " )\n", " text = gr.Textbox(lines=2, interactive=True, show_copy_button=True)\n", "\n", " with gr.Row():\n", " num = gr.Number(minimum=0, maximum=100, label=\"input\")\n", " out = gr.Number(label=\"output\")\n", " minimum_slider = gr.Slider(0, 100, 0, label=\"min\")\n", " maximum_slider = gr.Slider(0, 100, 100, label=\"max\")\n", " submit_btn = gr.Button(\"Submit\", variant=\"primary\")\n", "\n", " with gr.Row():\n", " country = gr.Dropdown(list(countries_cities_dict.keys()), label=\"Country\")\n", " cities = gr.Dropdown([], label=\"Cities\")\n", " \n", " @country.change(inputs=country, outputs=cities)\n", " def update_cities(country):\n", " cities = list(countries_cities_dict[country])\n", " return gr.Dropdown(choices=cities, value=cities[0], interactive=True)\n", "\n", " def reset_bounds(minimum, maximum):\n", " return gr.Number(minimum=minimum, maximum=maximum)\n", "\n", " radio.change(fn=change_textbox, inputs=radio, outputs=[text, submit_btn])\n", " gr.on(\n", " [minimum_slider.change, maximum_slider.change],\n", " reset_bounds,\n", " [minimum_slider, maximum_slider],\n", " outputs=num,\n", " )\n", " num.submit(lambda x: x, num, out)\n", "\n", "\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} \ No newline at end of file diff --git a/demos/blocks_essay/run.py b/demos/blocks_essay/run.py new file mode 100644 index 0000000000000000000000000000000000000000..2b2a313a9156c2a2f4a75ded74914e8823be2408 --- /dev/null +++ b/demos/blocks_essay/run.py @@ -0,0 +1,56 @@ +import gradio as gr + +countries_cities_dict = { + "USA": ["New York", "Los Angeles", "Chicago"], + "Canada": ["Toronto", "Montreal", "Vancouver"], + "Pakistan": ["Karachi", "Lahore", "Islamabad"], +} + + +def change_textbox(choice): + if choice == "short": + return gr.Textbox(lines=2, visible=True), gr.Button(interactive=True) + elif choice == "long": + return gr.Textbox(lines=8, visible=True, value="Lorem ipsum dolor sit amet"), gr.Button(interactive=True) + else: + return gr.Textbox(visible=False), gr.Button(interactive=False) + + +with gr.Blocks() as demo: + radio = gr.Radio( + ["short", "long", "none"], label="What kind of essay would you like to write?" + ) + text = gr.Textbox(lines=2, interactive=True, show_copy_button=True) + + with gr.Row(): + num = gr.Number(minimum=0, maximum=100, label="input") + out = gr.Number(label="output") + minimum_slider = gr.Slider(0, 100, 0, label="min") + maximum_slider = gr.Slider(0, 100, 100, label="max") + submit_btn = gr.Button("Submit", variant="primary") + + with gr.Row(): + country = gr.Dropdown(list(countries_cities_dict.keys()), label="Country") + cities = gr.Dropdown([], label="Cities") + + @country.change(inputs=country, outputs=cities) + def update_cities(country): + cities = list(countries_cities_dict[country]) + return gr.Dropdown(choices=cities, value=cities[0], interactive=True) + + def reset_bounds(minimum, maximum): + return gr.Number(minimum=minimum, maximum=maximum) + + radio.change(fn=change_textbox, inputs=radio, outputs=[text, submit_btn]) + gr.on( + [minimum_slider.change, maximum_slider.change], + reset_bounds, + [minimum_slider, maximum_slider], + outputs=num, + ) + num.submit(lambda x: x, num, out) + + + +if __name__ == "__main__": + demo.launch() diff --git a/demos/blocks_group/run.ipynb b/demos/blocks_group/run.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..15b658417cbf526d5be9a42d01b63c200c4b16a9 --- /dev/null +++ b/demos/blocks_group/run.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: blocks_group"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "\n", "def greet(name):\n", " return \"Hello \" + name + \"!\"\n", "\n", "with gr.Blocks() as demo:\n", " gr.Markdown(\"### This is a couple of elements without any gr.Group. Form elements naturally group together anyway.\")\n", " gr.Textbox(\"A\")\n", " gr.Number(3)\n", " gr.Button()\n", " gr.Image()\n", " gr.Slider()\n", "\n", " gr.Markdown(\"### This is the same set put in a gr.Group.\")\n", " with gr.Group():\n", " gr.Textbox(\"A\")\n", " gr.Number(3)\n", " gr.Button()\n", " gr.Image()\n", " gr.Slider()\n", "\n", " gr.Markdown(\"### Now in a Row, no group.\")\n", " with gr.Row():\n", " gr.Textbox(\"A\")\n", " gr.Number(3)\n", " gr.Button()\n", " gr.Image()\n", " gr.Slider()\n", "\n", " gr.Markdown(\"### Now in a Row in a group.\")\n", " with gr.Group():\n", " with gr.Row():\n", " gr.Textbox(\"A\")\n", " gr.Number(3)\n", " gr.Button()\n", " gr.Image()\n", " gr.Slider()\n", "\n", " gr.Markdown(\"### Several rows grouped together.\")\n", " with gr.Group():\n", " with gr.Row():\n", " gr.Textbox(\"A\")\n", " gr.Number(3)\n", " gr.Button()\n", " with gr.Row():\n", " gr.Image()\n", " gr.Audio()\n", "\n", " gr.Markdown(\"### Several columns grouped together. If columns are uneven, there is a gray group background.\")\n", " with gr.Group():\n", " with gr.Row():\n", " with gr.Column():\n", " name = gr.Textbox(label=\"Name\")\n", " btn = gr.Button(\"Hello\")\n", " gr.Dropdown([\"a\", \"b\", \"c\"], interactive=True)\n", " gr.Number()\n", " gr.Textbox()\n", " with gr.Column():\n", " gr.Image()\n", " gr.Dropdown([\"a\", \"b\", \"c\"], interactive=True)\n", " with gr.Row():\n", " gr.Number(scale=2)\n", " gr.Textbox()\n", "\n", " gr.Markdown(\"### container=False removes label, padding, and block border, placing elements 'directly' on background.\")\n", " gr.Radio([1,2,3], container=False)\n", " gr.Textbox(container=False)\n", " gr.Image(\"https://picsum.photos/id/237/200/300\", container=False, height=200)\n", "\n", " gr.Markdown(\"### Textbox, Dropdown, and Number input boxes takes up full space when within a group without a container.\")\n", "\n", "\n", " with gr.Group():\n", " name = gr.Textbox(label=\"Name\")\n", " output = gr.Textbox(show_label=False, container=False)\n", " greet_btn = gr.Button(\"Greet\")\n", " with gr.Row():\n", " gr.Dropdown([\"a\", \"b\", \"c\"], interactive=True, container=False)\n", " gr.Textbox(container=False)\n", " gr.Number(container=False)\n", " gr.Image(height=100)\n", " greet_btn.click(fn=greet, inputs=name, outputs=output, api_name=\"greet\")\n", "\n", "\n", " gr.Markdown(\"### More examples\")\n", "\n", " with gr.Group():\n", " gr.Chatbot()\n", " with gr.Row():\n", " name = gr.Textbox(label=\"Prompot\", container=False)\n", " go = gr.Button(\"go\", scale=0)\n", "\n", " with gr.Column():\n", " gr.Radio([1,2,3], container=False)\n", " gr.Slider(0, 20, container=False)\n", "\n", " with gr.Group():\n", " with gr.Row():\n", " gr.Dropdown([\"a\", \"b\", \"c\"], interactive=True, container=False, elem_id=\"here2\")\n", " gr.Number(container=False)\n", " gr.Textbox(container=False)\n", "\n", " with gr.Row():\n", " with gr.Column():\n", " gr.Dropdown([\"a\", \"b\", \"c\"], interactive=True, container=False, elem_id=\"here2\")\n", " with gr.Column():\n", " gr.Number(container=False)\n", " with gr.Column():\n", " gr.Textbox(container=False)\n", "\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} \ No newline at end of file diff --git a/demos/blocks_group/run.py b/demos/blocks_group/run.py new file mode 100644 index 0000000000000000000000000000000000000000..a5c5485891417c55d20c64f27ca751a170c93e5f --- /dev/null +++ b/demos/blocks_group/run.py @@ -0,0 +1,113 @@ +import gradio as gr + +def greet(name): + return "Hello " + name + "!" + +with gr.Blocks() as demo: + gr.Markdown("### This is a couple of elements without any gr.Group. Form elements naturally group together anyway.") + gr.Textbox("A") + gr.Number(3) + gr.Button() + gr.Image() + gr.Slider() + + gr.Markdown("### This is the same set put in a gr.Group.") + with gr.Group(): + gr.Textbox("A") + gr.Number(3) + gr.Button() + gr.Image() + gr.Slider() + + gr.Markdown("### Now in a Row, no group.") + with gr.Row(): + gr.Textbox("A") + gr.Number(3) + gr.Button() + gr.Image() + gr.Slider() + + gr.Markdown("### Now in a Row in a group.") + with gr.Group(): + with gr.Row(): + gr.Textbox("A") + gr.Number(3) + gr.Button() + gr.Image() + gr.Slider() + + gr.Markdown("### Several rows grouped together.") + with gr.Group(): + with gr.Row(): + gr.Textbox("A") + gr.Number(3) + gr.Button() + with gr.Row(): + gr.Image() + gr.Audio() + + gr.Markdown("### Several columns grouped together. If columns are uneven, there is a gray group background.") + with gr.Group(): + with gr.Row(): + with gr.Column(): + name = gr.Textbox(label="Name") + btn = gr.Button("Hello") + gr.Dropdown(["a", "b", "c"], interactive=True) + gr.Number() + gr.Textbox() + with gr.Column(): + gr.Image() + gr.Dropdown(["a", "b", "c"], interactive=True) + with gr.Row(): + gr.Number(scale=2) + gr.Textbox() + + gr.Markdown("### container=False removes label, padding, and block border, placing elements 'directly' on background.") + gr.Radio([1,2,3], container=False) + gr.Textbox(container=False) + gr.Image("https://picsum.photos/id/237/200/300", container=False, height=200) + + gr.Markdown("### Textbox, Dropdown, and Number input boxes takes up full space when within a group without a container.") + + + with gr.Group(): + name = gr.Textbox(label="Name") + output = gr.Textbox(show_label=False, container=False) + greet_btn = gr.Button("Greet") + with gr.Row(): + gr.Dropdown(["a", "b", "c"], interactive=True, container=False) + gr.Textbox(container=False) + gr.Number(container=False) + gr.Image(height=100) + greet_btn.click(fn=greet, inputs=name, outputs=output, api_name="greet") + + + gr.Markdown("### More examples") + + with gr.Group(): + gr.Chatbot() + with gr.Row(): + name = gr.Textbox(label="Prompot", container=False) + go = gr.Button("go", scale=0) + + with gr.Column(): + gr.Radio([1,2,3], container=False) + gr.Slider(0, 20, container=False) + + with gr.Group(): + with gr.Row(): + gr.Dropdown(["a", "b", "c"], interactive=True, container=False, elem_id="here2") + gr.Number(container=False) + gr.Textbox(container=False) + + with gr.Row(): + with gr.Column(): + gr.Dropdown(["a", "b", "c"], interactive=True, container=False, elem_id="here2") + with gr.Column(): + gr.Number(container=False) + with gr.Column(): + gr.Textbox(container=False) + + +if __name__ == "__main__": + demo.launch() \ No newline at end of file diff --git a/demos/blocks_js_methods/run.ipynb b/demos/blocks_js_methods/run.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..1a5195c09b6de1ce5d3510e0a47eb1d1aa1e1d65 --- /dev/null +++ b/demos/blocks_js_methods/run.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: blocks_js_methods"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "\n", "blocks = gr.Blocks()\n", "\n", "with blocks as demo:\n", " subject = gr.Textbox(placeholder=\"subject\")\n", " verb = gr.Radio([\"ate\", \"loved\", \"hated\"])\n", " object = gr.Textbox(placeholder=\"object\")\n", "\n", " with gr.Row():\n", " btn = gr.Button(\"Create sentence.\")\n", " reverse_btn = gr.Button(\"Reverse sentence.\")\n", " foo_bar_btn = gr.Button(\"Append foo\")\n", " reverse_then_to_the_server_btn = gr.Button(\n", " \"Reverse sentence and send to server.\"\n", " )\n", "\n", " def sentence_maker(w1, w2, w3):\n", " return f\"{w1} {w2} {w3}\"\n", "\n", " output1 = gr.Textbox(label=\"output 1\")\n", " output2 = gr.Textbox(label=\"verb\")\n", " output3 = gr.Textbox(label=\"verb reversed\")\n", " output4 = gr.Textbox(label=\"front end process and then send to backend\")\n", "\n", " btn.click(sentence_maker, [subject, verb, object], output1)\n", " reverse_btn.click(\n", " None, [subject, verb, object], output2, js=\"(s, v, o) => o + ' ' + v + ' ' + s\"\n", " )\n", " verb.change(lambda x: x, verb, output3, js=\"(x) => [...x].reverse().join('')\")\n", " foo_bar_btn.click(None, [], subject, js=\"(x) => x + ' foo'\")\n", "\n", " reverse_then_to_the_server_btn.click(\n", " sentence_maker,\n", " [subject, verb, object],\n", " output4,\n", " js=\"(s, v, o) => [s, v, o].map(x => [...x].reverse().join(''))\",\n", " )\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} \ No newline at end of file diff --git a/demos/blocks_js_methods/run.py b/demos/blocks_js_methods/run.py new file mode 100644 index 0000000000000000000000000000000000000000..2abb2d9d3bca4114009da9ae61ef1ebfc347da81 --- /dev/null +++ b/demos/blocks_js_methods/run.py @@ -0,0 +1,41 @@ +import gradio as gr + +blocks = gr.Blocks() + +with blocks as demo: + subject = gr.Textbox(placeholder="subject") + verb = gr.Radio(["ate", "loved", "hated"]) + object = gr.Textbox(placeholder="object") + + with gr.Row(): + btn = gr.Button("Create sentence.") + reverse_btn = gr.Button("Reverse sentence.") + foo_bar_btn = gr.Button("Append foo") + reverse_then_to_the_server_btn = gr.Button( + "Reverse sentence and send to server." + ) + + def sentence_maker(w1, w2, w3): + return f"{w1} {w2} {w3}" + + output1 = gr.Textbox(label="output 1") + output2 = gr.Textbox(label="verb") + output3 = gr.Textbox(label="verb reversed") + output4 = gr.Textbox(label="front end process and then send to backend") + + btn.click(sentence_maker, [subject, verb, object], output1) + reverse_btn.click( + None, [subject, verb, object], output2, js="(s, v, o) => o + ' ' + v + ' ' + s" + ) + verb.change(lambda x: x, verb, output3, js="(x) => [...x].reverse().join('')") + foo_bar_btn.click(None, [], subject, js="(x) => x + ' foo'") + + reverse_then_to_the_server_btn.click( + sentence_maker, + [subject, verb, object], + output4, + js="(s, v, o) => [s, v, o].map(x => [...x].reverse().join(''))", + ) + +if __name__ == "__main__": + demo.launch() diff --git a/demos/blocks_layout/run.ipynb b/demos/blocks_layout/run.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..deef224dfb4132575a2a5fe9c18e7978cb742132 --- /dev/null +++ b/demos/blocks_layout/run.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: blocks_layout"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "\n", "\n", "demo = gr.Blocks()\n", "\n", "with demo:\n", " with gr.Row():\n", " gr.Image(interactive=True, scale=2)\n", " gr.Image()\n", " with gr.Row():\n", " gr.Textbox(label=\"Text\")\n", " gr.Number(label=\"Count\", scale=2)\n", " gr.Radio(choices=[\"One\", \"Two\"])\n", " with gr.Row():\n", " gr.Button(\"500\", scale=0, min_width=500)\n", " gr.Button(\"A\", scale=0)\n", " gr.Button(\"grow\")\n", " with gr.Row():\n", " gr.Textbox()\n", " gr.Textbox()\n", " gr.Button() \n", " with gr.Row():\n", " with gr.Row():\n", " with gr.Column():\n", " gr.Textbox(label=\"Text\")\n", " gr.Number(label=\"Count\")\n", " gr.Radio(choices=[\"One\", \"Two\"])\n", " gr.Image()\n", " with gr.Column():\n", " gr.Image(interactive=True)\n", " gr.Image()\n", " gr.Image()\n", " gr.Textbox(label=\"Text\")\n", " gr.Number(label=\"Count\")\n", " gr.Radio(choices=[\"One\", \"Two\"])\n", "\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} \ No newline at end of file diff --git a/demos/blocks_layout/run.py b/demos/blocks_layout/run.py new file mode 100644 index 0000000000000000000000000000000000000000..6a7f3660ffce75035d191274fecf3063f28b647d --- /dev/null +++ b/demos/blocks_layout/run.py @@ -0,0 +1,39 @@ +import gradio as gr + + +demo = gr.Blocks() + +with demo: + with gr.Row(): + gr.Image(interactive=True, scale=2) + gr.Image() + with gr.Row(): + gr.Textbox(label="Text") + gr.Number(label="Count", scale=2) + gr.Radio(choices=["One", "Two"]) + with gr.Row(): + gr.Button("500", scale=0, min_width=500) + gr.Button("A", scale=0) + gr.Button("grow") + with gr.Row(): + gr.Textbox() + gr.Textbox() + gr.Button() + with gr.Row(): + with gr.Row(): + with gr.Column(): + gr.Textbox(label="Text") + gr.Number(label="Count") + gr.Radio(choices=["One", "Two"]) + gr.Image() + with gr.Column(): + gr.Image(interactive=True) + gr.Image() + gr.Image() + gr.Textbox(label="Text") + gr.Number(label="Count") + gr.Radio(choices=["One", "Two"]) + + +if __name__ == "__main__": + demo.launch() diff --git a/demos/blocks_multiple_event_triggers/requirements.txt b/demos/blocks_multiple_event_triggers/requirements.txt new file mode 100644 index 0000000000000000000000000000000000000000..5cb63bcc8c366f4abc569ed8ef379a90d4759ff4 --- /dev/null +++ b/demos/blocks_multiple_event_triggers/requirements.txt @@ -0,0 +1,2 @@ +plotly +pypistats \ No newline at end of file diff --git a/demos/blocks_multiple_event_triggers/run.ipynb b/demos/blocks_multiple_event_triggers/run.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..1ada4f02c5276bfb454f57e163052181e5af9d93 --- /dev/null +++ b/demos/blocks_multiple_event_triggers/run.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: blocks_multiple_event_triggers"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio plotly pypistats"]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import pypistats\n", "from datetime import date\n", "from dateutil.relativedelta import relativedelta\n", "import pandas as pd\n", "\n", "def get_plot(lib, time):\n", " data = pypistats.overall(lib, total=True, format=\"pandas\")\n", " data = data.groupby(\"category\").get_group(\"with_mirrors\").sort_values(\"date\")\n", " start_date = date.today() - relativedelta(months=int(time.split(\" \")[0]))\n", " data = data[(data['date'] > str(start_date))]\n", " data.date = pd.to_datetime(pd.to_datetime(data.date))\n", " return gr.LinePlot(value=data, x=\"date\", y=\"downloads\",\n", " tooltip=['date', 'downloads'],\n", " title=f\"Pypi downloads of {lib} over last {time}\",\n", " overlay_point=True,\n", " height=400,\n", " width=900)\n", "\n", "\n", "with gr.Blocks() as demo:\n", " gr.Markdown(\n", " \"\"\"\n", " ## Pypi Download Stats \ud83d\udcc8\n", " See live download stats for all of Hugging Face's open-source libraries \ud83e\udd17\n", " \"\"\")\n", " with gr.Row():\n", " lib = gr.Dropdown([\"transformers\", \"datasets\", \"huggingface-hub\", \"gradio\", \"accelerate\"],\n", " value=\"gradio\", label=\"Library\")\n", " time = gr.Dropdown([\"3 months\", \"6 months\", \"9 months\", \"12 months\"],\n", " value=\"3 months\", label=\"Downloads over the last...\")\n", "\n", " plt = gr.LinePlot()\n", " # You can add multiple event triggers in 2 lines like this\n", " for event in [lib.change, time.change, demo.load]:\n", " event(get_plot, [lib, time], [plt])\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} \ No newline at end of file diff --git a/demos/blocks_multiple_event_triggers/run.py b/demos/blocks_multiple_event_triggers/run.py new file mode 100644 index 0000000000000000000000000000000000000000..a8340d8f760e90b0ce571c751cc2c98813e1dbca --- /dev/null +++ b/demos/blocks_multiple_event_triggers/run.py @@ -0,0 +1,39 @@ +import gradio as gr +import pypistats +from datetime import date +from dateutil.relativedelta import relativedelta +import pandas as pd + +def get_plot(lib, time): + data = pypistats.overall(lib, total=True, format="pandas") + data = data.groupby("category").get_group("with_mirrors").sort_values("date") + start_date = date.today() - relativedelta(months=int(time.split(" ")[0])) + data = data[(data['date'] > str(start_date))] + data.date = pd.to_datetime(pd.to_datetime(data.date)) + return gr.LinePlot(value=data, x="date", y="downloads", + tooltip=['date', 'downloads'], + title=f"Pypi downloads of {lib} over last {time}", + overlay_point=True, + height=400, + width=900) + + +with gr.Blocks() as demo: + gr.Markdown( + """ + ## Pypi Download Stats 📈 + See live download stats for all of Hugging Face's open-source libraries 🤗 + """) + with gr.Row(): + lib = gr.Dropdown(["transformers", "datasets", "huggingface-hub", "gradio", "accelerate"], + value="gradio", label="Library") + time = gr.Dropdown(["3 months", "6 months", "9 months", "12 months"], + value="3 months", label="Downloads over the last...") + + plt = gr.LinePlot() + # You can add multiple event triggers in 2 lines like this + for event in [lib.change, time.change, demo.load]: + event(get_plot, [lib, time], [plt]) + +if __name__ == "__main__": + demo.launch() diff --git a/demos/blocks_update/run.ipynb b/demos/blocks_update/run.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..31eb77c2f3c4d6997da61c5f71e58c8643da98f8 --- /dev/null +++ b/demos/blocks_update/run.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: blocks_update"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "\n", "with gr.Blocks() as demo:\n", " gr.Markdown(\n", " \"\"\"\n", " # Animal Generator\n", " Once you select a species, the detail panel should be visible.\n", " \"\"\"\n", " )\n", "\n", " species = gr.Radio(label=\"Animal Class\", choices=[\"Mammal\", \"Fish\", \"Bird\"])\n", " animal = gr.Dropdown(label=\"Animal\", choices=[])\n", "\n", " with gr.Column(visible=False) as details_col:\n", " weight = gr.Slider(0, 20)\n", " details = gr.Textbox(label=\"Extra Details\")\n", " generate_btn = gr.Button(\"Generate\")\n", " output = gr.Textbox(label=\"Output\")\n", "\n", " species_map = {\n", " \"Mammal\": [\"Elephant\", \"Giraffe\", \"Hamster\"],\n", " \"Fish\": [\"Shark\", \"Salmon\", \"Tuna\"],\n", " \"Bird\": [\"Chicken\", \"Eagle\", \"Hawk\"],\n", " }\n", "\n", " def filter_species(species):\n", " return gr.Dropdown(\n", " choices=species_map[species], value=species_map[species][1]\n", " ), gr.Column(visible=True)\n", "\n", " species.change(filter_species, species, [animal, details_col])\n", "\n", " def filter_weight(animal):\n", " if animal in (\"Elephant\", \"Shark\", \"Giraffe\"):\n", " return gr.Slider(maximum=100)\n", " else:\n", " return gr.Slider(maximum=20)\n", "\n", " animal.change(filter_weight, animal, weight)\n", " weight.change(lambda w: gr.Textbox(lines=int(w / 10) + 1), weight, details)\n", "\n", " generate_btn.click(lambda x: x, details, output)\n", "\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} \ No newline at end of file diff --git a/demos/blocks_update/run.py b/demos/blocks_update/run.py new file mode 100644 index 0000000000000000000000000000000000000000..423a8d3dce27590f84d1a37ec9f31f2df0bde631 --- /dev/null +++ b/demos/blocks_update/run.py @@ -0,0 +1,46 @@ +import gradio as gr + +with gr.Blocks() as demo: + gr.Markdown( + """ + # Animal Generator + Once you select a species, the detail panel should be visible. + """ + ) + + species = gr.Radio(label="Animal Class", choices=["Mammal", "Fish", "Bird"]) + animal = gr.Dropdown(label="Animal", choices=[]) + + with gr.Column(visible=False) as details_col: + weight = gr.Slider(0, 20) + details = gr.Textbox(label="Extra Details") + generate_btn = gr.Button("Generate") + output = gr.Textbox(label="Output") + + species_map = { + "Mammal": ["Elephant", "Giraffe", "Hamster"], + "Fish": ["Shark", "Salmon", "Tuna"], + "Bird": ["Chicken", "Eagle", "Hawk"], + } + + def filter_species(species): + return gr.Dropdown( + choices=species_map[species], value=species_map[species][1] + ), gr.Column(visible=True) + + species.change(filter_species, species, [animal, details_col]) + + def filter_weight(animal): + if animal in ("Elephant", "Shark", "Giraffe"): + return gr.Slider(maximum=100) + else: + return gr.Slider(maximum=20) + + animal.change(filter_weight, animal, weight) + weight.change(lambda w: gr.Textbox(lines=int(w / 10) + 1), weight, details) + + generate_btn.click(lambda x: x, details, output) + + +if __name__ == "__main__": + demo.launch() \ No newline at end of file diff --git a/demos/calculator/examples/log.csv b/demos/calculator/examples/log.csv new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/demos/calculator/run.ipynb b/demos/calculator/run.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..f43bbf4ce843d1b75f8b84cba738fcd9c7ba0ace --- /dev/null +++ b/demos/calculator/run.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: calculator"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "os.mkdir('examples')\n", "!wget -q -O examples/log.csv https://github.com/gradio-app/gradio/raw/main/demo/calculator/examples/log.csv"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "#from foo import BAR\n", "#\n", "def calculator(num1, operation, num2):\n", " if operation == \"add\":\n", " return num1 + num2\n", " elif operation == \"subtract\":\n", " return num1 - num2\n", " elif operation == \"multiply\":\n", " return num1 * num2\n", " elif operation == \"divide\":\n", " if num2 == 0:\n", " raise gr.Error(\"Cannot divide by zero!\")\n", " return num1 / num2\n", "\n", "demo = gr.Interface(\n", " calculator,\n", " [\n", " \"number\", \n", " gr.Radio([\"add\", \"subtract\", \"multiply\", \"divide\"]),\n", " \"number\"\n", " ],\n", " \"number\",\n", " examples=[\n", " [45, \"add\", 3],\n", " [3.14, \"divide\", 2],\n", " [144, \"multiply\", 2.5],\n", " [0, \"subtract\", 1.2],\n", " ],\n", " title=\"Toy Calculator\",\n", " description=\"Here's a sample toy calculator. Allows you to calculate things like $2+2=4$\",\n", ")\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} \ No newline at end of file diff --git a/demos/calculator/run.py b/demos/calculator/run.py new file mode 100644 index 0000000000000000000000000000000000000000..9ee04812fac61aa54de6f73d6cb1baff35110149 --- /dev/null +++ b/demos/calculator/run.py @@ -0,0 +1,35 @@ +import gradio as gr +#from foo import BAR +# +def calculator(num1, operation, num2): + if operation == "add": + return num1 + num2 + elif operation == "subtract": + return num1 - num2 + elif operation == "multiply": + return num1 * num2 + elif operation == "divide": + if num2 == 0: + raise gr.Error("Cannot divide by zero!") + return num1 / num2 + +demo = gr.Interface( + calculator, + [ + "number", + gr.Radio(["add", "subtract", "multiply", "divide"]), + "number" + ], + "number", + examples=[ + [45, "add", 3], + [3.14, "divide", 2], + [144, "multiply", 2.5], + [0, "subtract", 1.2], + ], + title="Toy Calculator", + description="Here's a sample toy calculator. Allows you to calculate things like $2+2=4$", +) + +if __name__ == "__main__": + demo.launch() diff --git a/demos/calculator/screenshot.gif b/demos/calculator/screenshot.gif new file mode 100644 index 0000000000000000000000000000000000000000..8ae0d0494adf069b4e23cf30956b43262258021c --- /dev/null +++ b/demos/calculator/screenshot.gif @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3698fb03b6507ff954de47559f6830dfff88aa66487d2029a9bcf1c2f3762e08 +size 5718090 diff --git a/demos/cancel_events/run.ipynb b/demos/cancel_events/run.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..d2b61c048a4b053357cec4ff7e32de7773f4a946 --- /dev/null +++ b/demos/cancel_events/run.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: cancel_events"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import time\n", "import gradio as gr\n", "import atexit\n", "import pathlib\n", "\n", "log_file = (pathlib.Path(__file__).parent / \"cancel_events_output_log.txt\").resolve()\n", "\n", "def fake_diffusion(steps):\n", " log_file.write_text(\"\")\n", " for i in range(steps):\n", " print(f\"Current step: {i}\")\n", " with log_file.open(\"a\") as f:\n", " f.write(f\"Current step: {i}\\n\")\n", " time.sleep(0.2)\n", " yield str(i)\n", "\n", "\n", "def long_prediction(*args, **kwargs):\n", " time.sleep(10)\n", " return 42\n", "\n", "\n", "with gr.Blocks() as demo:\n", " with gr.Row():\n", " with gr.Column():\n", " n = gr.Slider(1, 10, value=9, step=1, label=\"Number Steps\")\n", " run = gr.Button(value=\"Start Iterating\")\n", " output = gr.Textbox(label=\"Iterative Output\")\n", " stop = gr.Button(value=\"Stop Iterating\")\n", " with gr.Column():\n", " textbox = gr.Textbox(label=\"Prompt\")\n", " prediction = gr.Number(label=\"Expensive Calculation\")\n", " run_pred = gr.Button(value=\"Run Expensive Calculation\")\n", " with gr.Column():\n", " cancel_on_change = gr.Textbox(label=\"Cancel Iteration and Expensive Calculation on Change\")\n", " cancel_on_submit = gr.Textbox(label=\"Cancel Iteration and Expensive Calculation on Submit\")\n", " echo = gr.Textbox(label=\"Echo\")\n", " with gr.Row():\n", " with gr.Column():\n", " image = gr.Image(sources=[\"webcam\"], label=\"Cancel on clear\", interactive=True)\n", " with gr.Column():\n", " video = gr.Video(sources=[\"webcam\"], label=\"Cancel on start recording\", interactive=True)\n", "\n", " click_event = run.click(fake_diffusion, n, output)\n", " stop.click(fn=None, inputs=None, outputs=None, cancels=[click_event])\n", " pred_event = run_pred.click(fn=long_prediction, inputs=[textbox], outputs=prediction)\n", "\n", " cancel_on_change.change(None, None, None, cancels=[click_event, pred_event])\n", " cancel_on_submit.submit(lambda s: s, cancel_on_submit, echo, cancels=[click_event, pred_event])\n", " image.clear(None, None, None, cancels=[click_event, pred_event])\n", " video.start_recording(None, None, None, cancels=[click_event, pred_event])\n", "\n", " demo.queue(max_size=20)\n", " atexit.register(lambda: log_file.unlink())\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} \ No newline at end of file diff --git a/demos/cancel_events/run.py b/demos/cancel_events/run.py new file mode 100644 index 0000000000000000000000000000000000000000..409858c5748a3f458fb6a78f29570e4d0180a0a0 --- /dev/null +++ b/demos/cancel_events/run.py @@ -0,0 +1,57 @@ +import time +import gradio as gr +import atexit +import pathlib + +log_file = (pathlib.Path(__file__).parent / "cancel_events_output_log.txt").resolve() + +def fake_diffusion(steps): + log_file.write_text("") + for i in range(steps): + print(f"Current step: {i}") + with log_file.open("a") as f: + f.write(f"Current step: {i}\n") + time.sleep(0.2) + yield str(i) + + +def long_prediction(*args, **kwargs): + time.sleep(10) + return 42 + + +with gr.Blocks() as demo: + with gr.Row(): + with gr.Column(): + n = gr.Slider(1, 10, value=9, step=1, label="Number Steps") + run = gr.Button(value="Start Iterating") + output = gr.Textbox(label="Iterative Output") + stop = gr.Button(value="Stop Iterating") + with gr.Column(): + textbox = gr.Textbox(label="Prompt") + prediction = gr.Number(label="Expensive Calculation") + run_pred = gr.Button(value="Run Expensive Calculation") + with gr.Column(): + cancel_on_change = gr.Textbox(label="Cancel Iteration and Expensive Calculation on Change") + cancel_on_submit = gr.Textbox(label="Cancel Iteration and Expensive Calculation on Submit") + echo = gr.Textbox(label="Echo") + with gr.Row(): + with gr.Column(): + image = gr.Image(sources=["webcam"], label="Cancel on clear", interactive=True) + with gr.Column(): + video = gr.Video(sources=["webcam"], label="Cancel on start recording", interactive=True) + + click_event = run.click(fake_diffusion, n, output) + stop.click(fn=None, inputs=None, outputs=None, cancels=[click_event]) + pred_event = run_pred.click(fn=long_prediction, inputs=[textbox], outputs=prediction) + + cancel_on_change.change(None, None, None, cancels=[click_event, pred_event]) + cancel_on_submit.submit(lambda s: s, cancel_on_submit, echo, cancels=[click_event, pred_event]) + image.clear(None, None, None, cancels=[click_event, pred_event]) + video.start_recording(None, None, None, cancels=[click_event, pred_event]) + + demo.queue(max_size=20) + atexit.register(lambda: log_file.unlink()) + +if __name__ == "__main__": + demo.launch() diff --git a/demos/chatbot_multimodal/files/avatar.png b/demos/chatbot_multimodal/files/avatar.png new file mode 100644 index 0000000000000000000000000000000000000000..8f1df7156f0a690a2415903061e19c20e24adac4 Binary files /dev/null and b/demos/chatbot_multimodal/files/avatar.png differ diff --git a/demos/chatbot_multimodal/files/lion.jpg b/demos/chatbot_multimodal/files/lion.jpg new file mode 100644 index 0000000000000000000000000000000000000000..e9bf9f5d0816d6201b4862088dc74476249a6a70 Binary files /dev/null and b/demos/chatbot_multimodal/files/lion.jpg differ diff --git a/demos/chatbot_multimodal/run.ipynb b/demos/chatbot_multimodal/run.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..9995e6df9b0efd5b2c41550ce6cacbaece50eec8 --- /dev/null +++ b/demos/chatbot_multimodal/run.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: chatbot_multimodal"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "os.mkdir('files')\n", "!wget -q -O files/avatar.png https://github.com/gradio-app/gradio/raw/main/demo/chatbot_multimodal/files/avatar.png\n", "!wget -q -O files/lion.jpg https://github.com/gradio-app/gradio/raw/main/demo/chatbot_multimodal/files/lion.jpg"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import os\n", "import time\n", "\n", "# Chatbot demo with multimodal input (text, markdown, LaTeX, code blocks, image, audio, & video). Plus shows support for streaming text.\n", "\n", "\n", "def print_like_dislike(x: gr.LikeData):\n", " print(x.index, x.value, x.liked)\n", "\n", "def add_message(history, message):\n", " for x in message[\"files\"]:\n", " history.append(((x,), None))\n", " if message[\"text\"] is not None:\n", " history.append((message[\"text\"], None))\n", " return history, gr.MultimodalTextbox(value=None, interactive=False)\n", "\n", "def bot(history):\n", " response = \"**That's cool!**\"\n", " history[-1][1] = \"\"\n", " for character in response:\n", " history[-1][1] += character\n", " time.sleep(0.05)\n", " yield history\n", "\n", "with gr.Blocks() as demo:\n", " chatbot = gr.Chatbot(\n", " [],\n", " elem_id=\"chatbot\",\n", " bubble_full_width=False\n", " )\n", "\n", " chat_input = gr.MultimodalTextbox(interactive=True, file_types=[\"image\"], placeholder=\"Enter message or upload file...\", show_label=False)\n", "\n", " chat_msg = chat_input.submit(add_message, [chatbot, chat_input], [chatbot, chat_input])\n", " bot_msg = chat_msg.then(bot, chatbot, chatbot, api_name=\"bot_response\")\n", " bot_msg.then(lambda: gr.MultimodalTextbox(interactive=True), None, [chat_input])\n", "\n", " chatbot.like(print_like_dislike, None, None)\n", "\n", "demo.queue()\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} \ No newline at end of file diff --git a/demos/chatbot_multimodal/run.py b/demos/chatbot_multimodal/run.py new file mode 100644 index 0000000000000000000000000000000000000000..650172edc357371815eb275bf29a3464b7eaeece --- /dev/null +++ b/demos/chatbot_multimodal/run.py @@ -0,0 +1,43 @@ +import gradio as gr +import os +import time + +# Chatbot demo with multimodal input (text, markdown, LaTeX, code blocks, image, audio, & video). Plus shows support for streaming text. + + +def print_like_dislike(x: gr.LikeData): + print(x.index, x.value, x.liked) + +def add_message(history, message): + for x in message["files"]: + history.append(((x,), None)) + if message["text"] is not None: + history.append((message["text"], None)) + return history, gr.MultimodalTextbox(value=None, interactive=False) + +def bot(history): + response = "**That's cool!**" + history[-1][1] = "" + for character in response: + history[-1][1] += character + time.sleep(0.05) + yield history + +with gr.Blocks() as demo: + chatbot = gr.Chatbot( + [], + elem_id="chatbot", + bubble_full_width=False + ) + + chat_input = gr.MultimodalTextbox(interactive=True, file_types=["image"], placeholder="Enter message or upload file...", show_label=False) + + chat_msg = chat_input.submit(add_message, [chatbot, chat_input], [chatbot, chat_input]) + bot_msg = chat_msg.then(bot, chatbot, chatbot, api_name="bot_response") + bot_msg.then(lambda: gr.MultimodalTextbox(interactive=True), None, [chat_input]) + + chatbot.like(print_like_dislike, None, None) + +demo.queue() +if __name__ == "__main__": + demo.launch() diff --git a/demos/chatinterface_streaming_echo/run.ipynb b/demos/chatinterface_streaming_echo/run.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..2c14e865d53e39c37c1f22fcfd03c25f253e637a --- /dev/null +++ b/demos/chatinterface_streaming_echo/run.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: chatinterface_streaming_echo"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import time\n", "import gradio as gr\n", "\n", "\n", "def slow_echo(message, history):\n", " for i in range(len(message)):\n", " time.sleep(0.05)\n", " yield \"You typed: \" + message[: i + 1]\n", "\n", "\n", "demo = gr.ChatInterface(slow_echo).queue()\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} \ No newline at end of file diff --git a/demos/chatinterface_streaming_echo/run.py b/demos/chatinterface_streaming_echo/run.py new file mode 100644 index 0000000000000000000000000000000000000000..ffda9c586f63beb93c66c4aabd979d29a7f12819 --- /dev/null +++ b/demos/chatinterface_streaming_echo/run.py @@ -0,0 +1,14 @@ +import time +import gradio as gr + + +def slow_echo(message, history): + for i in range(len(message)): + time.sleep(0.05) + yield "You typed: " + message[: i + 1] + + +demo = gr.ChatInterface(slow_echo).queue() + +if __name__ == "__main__": + demo.launch() diff --git a/demos/clear_components/__init__.py b/demos/clear_components/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/demos/clear_components/run.ipynb b/demos/clear_components/run.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..5593dd49a72252fe47bdb5935933140ff26d0e39 --- /dev/null +++ b/demos/clear_components/run.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: clear_components"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/clear_components/__init__.py"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "from datetime import datetime\n", "import os\n", "import random\n", "import string\n", "import pandas as pd\n", "\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "\n", "\n", "\n", "def random_plot():\n", " start_year = 2020\n", " x = np.arange(start_year, start_year + 5)\n", " year_count = x.shape[0]\n", " plt_format = \"-\"\n", " fig = plt.figure()\n", " ax = fig.add_subplot(111)\n", " series = np.arange(0, year_count, dtype=float)\n", " series = series**2\n", " series += np.random.rand(year_count)\n", " ax.plot(x, series, plt_format)\n", " return fig\n", "\n", "\n", "images = [\n", " \"https://images.unsplash.com/photo-1507003211169-0a1dd7228f2d?ixlib=rb-1.2.1&ixid=MnwxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8&auto=format&fit=crop&w=387&q=80\",\n", " \"https://images.unsplash.com/photo-1554151228-14d9def656e4?ixlib=rb-1.2.1&ixid=MnwxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8&auto=format&fit=crop&w=386&q=80\",\n", " \"https://images.unsplash.com/photo-1542909168-82c3e7fdca5c?ixlib=rb-1.2.1&ixid=MnwxMjA3fDB8MHxzZWFyY2h8MXx8aHVtYW4lMjBmYWNlfGVufDB8fDB8fA%3D%3D&w=1000&q=80\",\n", "]\n", "file_dir = os.path.join(os.path.abspath(''), \"..\", \"kitchen_sink\", \"files\")\n", "model3d_dir = os.path.join(os.path.abspath(''), \"..\", \"model3D\", \"files\")\n", "highlighted_text_output_1 = [\n", " {\n", " \"entity\": \"I-LOC\",\n", " \"score\": 0.9988978,\n", " \"index\": 2,\n", " \"word\": \"Chicago\",\n", " \"start\": 5,\n", " \"end\": 12,\n", " },\n", " {\n", " \"entity\": \"I-MISC\",\n", " \"score\": 0.9958592,\n", " \"index\": 5,\n", " \"word\": \"Pakistani\",\n", " \"start\": 22,\n", " \"end\": 31,\n", " },\n", "]\n", "highlighted_text_output_2 = [\n", " {\n", " \"entity\": \"I-LOC\",\n", " \"score\": 0.9988978,\n", " \"index\": 2,\n", " \"word\": \"Chicago\",\n", " \"start\": 5,\n", " \"end\": 12,\n", " },\n", " {\n", " \"entity\": \"I-LOC\",\n", " \"score\": 0.9958592,\n", " \"index\": 5,\n", " \"word\": \"Pakistan\",\n", " \"start\": 22,\n", " \"end\": 30,\n", " },\n", "]\n", "\n", "highlighted_text = \"Does Chicago have any Pakistani restaurants\"\n", "\n", "\n", "def random_model3d():\n", " model_3d = random.choice(\n", " [os.path.join(model3d_dir, model) for model in os.listdir(model3d_dir) if model != \"source.txt\"]\n", " )\n", " return model_3d\n", "\n", "\n", "\n", "components = [\n", " gr.Textbox(value=lambda: datetime.now(), label=\"Current Time\"),\n", " gr.Number(value=lambda: random.random(), label=\"Random Percentage\"),\n", " gr.Slider(minimum=0, maximum=100, randomize=True, label=\"Slider with randomize\"),\n", " gr.Slider(\n", " minimum=0,\n", " maximum=1,\n", " value=lambda: random.random(),\n", " label=\"Slider with value func\",\n", " ),\n", " gr.Checkbox(value=lambda: random.random() > 0.5, label=\"Random Checkbox\"),\n", " gr.CheckboxGroup(\n", " choices=[\"a\", \"b\", \"c\", \"d\"],\n", " value=lambda: random.choice([\"a\", \"b\", \"c\", \"d\"]),\n", " label=\"Random CheckboxGroup\",\n", " ),\n", " gr.Radio(\n", " choices=list(string.ascii_lowercase),\n", " value=lambda: random.choice(string.ascii_lowercase),\n", " ),\n", " gr.Dropdown(\n", " choices=[\"a\", \"b\", \"c\", \"d\", \"e\"],\n", " value=lambda: random.choice([\"a\", \"b\", \"c\"]),\n", " ),\n", " gr.Image(\n", " value=lambda: random.choice(images)\n", " ),\n", " gr.Video(value=lambda: os.path.join(file_dir, \"world.mp4\")),\n", " gr.Audio(value=lambda: os.path.join(file_dir, \"cantina.wav\")),\n", " gr.File(\n", " value=lambda: random.choice(\n", " [os.path.join(file_dir, img) for img in os.listdir(file_dir)]\n", " )\n", " ),\n", " gr.Dataframe(\n", " value=lambda: pd.DataFrame({\"random_number_rows\": range(5)}, columns=[\"one\", \"two\", \"three\"])\n", " ),\n", " gr.ColorPicker(value=lambda: random.choice([\"#000000\", \"#ff0000\", \"#0000FF\"])),\n", " gr.Label(value=lambda: random.choice([\"Pedestrian\", \"Car\", \"Cyclist\"])),\n", " gr.HighlightedText(\n", " value=lambda: random.choice(\n", " [\n", " {\"text\": highlighted_text, \"entities\": highlighted_text_output_1},\n", " {\"text\": highlighted_text, \"entities\": highlighted_text_output_2},\n", " ]\n", " ),\n", " ),\n", " gr.JSON(value=lambda: random.choice([{\"a\": 1}, {\"b\": 2}])),\n", " gr.HTML(\n", " value=lambda: random.choice(\n", " [\n", " '

I am red

',\n", " '

I am blue

',\n", " ]\n", " )\n", " ),\n", " gr.Gallery(\n", " value=lambda: images\n", " ),\n", " gr.Model3D(value=random_model3d),\n", " gr.Plot(value=random_plot),\n", " gr.Markdown(value=lambda: f\"### {random.choice(['Hello', 'Hi', 'Goodbye!'])}\"),\n", "]\n", "\n", "\n", "def evaluate_values(*args):\n", " are_false = []\n", " for a in args:\n", " if isinstance(a, (pd.DataFrame, np.ndarray)):\n", " are_false.append(not a.any().any())\n", " elif isinstance(a, str) and a.startswith(\"#\"):\n", " are_false.append(a == \"#000000\")\n", " else:\n", " are_false.append(not a)\n", " return all(are_false)\n", "\n", "\n", "with gr.Blocks() as demo:\n", " for i, component in enumerate(components):\n", " component.label = f\"component_{str(i).zfill(2)}\"\n", " component.render()\n", " clear = gr.ClearButton(value=\"Clear\", components=components)\n", " result = gr.Textbox(label=\"Are all cleared?\")\n", " hide = gr.Button(value=\"Hide\")\n", " reveal = gr.Button(value=\"Reveal\")\n", " clear_button_and_components = components + [clear]\n", " hide.click(\n", " lambda: [c.__class__(visible=False) for c in clear_button_and_components],\n", " inputs=[],\n", " outputs=clear_button_and_components\n", " )\n", " reveal.click(\n", " lambda: [c.__class__(visible=True) for c in clear_button_and_components],\n", " inputs=[],\n", " outputs=clear_button_and_components\n", " )\n", " get_value = gr.Button(value=\"Get Values\")\n", " get_value.click(evaluate_values, components, result)\n", "\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} \ No newline at end of file diff --git a/demos/clear_components/run.py b/demos/clear_components/run.py new file mode 100644 index 0000000000000000000000000000000000000000..3965ac64bca7e7e4ed6d93c67739d9f6a5dc5f8c --- /dev/null +++ b/demos/clear_components/run.py @@ -0,0 +1,183 @@ +import gradio as gr +from datetime import datetime +import os +import random +import string +import pandas as pd + +import numpy as np +import matplotlib.pyplot as plt + + + +def random_plot(): + start_year = 2020 + x = np.arange(start_year, start_year + 5) + year_count = x.shape[0] + plt_format = "-" + fig = plt.figure() + ax = fig.add_subplot(111) + series = np.arange(0, year_count, dtype=float) + series = series**2 + series += np.random.rand(year_count) + ax.plot(x, series, plt_format) + return fig + + +images = [ + "https://images.unsplash.com/photo-1507003211169-0a1dd7228f2d?ixlib=rb-1.2.1&ixid=MnwxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8&auto=format&fit=crop&w=387&q=80", + "https://images.unsplash.com/photo-1554151228-14d9def656e4?ixlib=rb-1.2.1&ixid=MnwxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8&auto=format&fit=crop&w=386&q=80", + "https://images.unsplash.com/photo-1542909168-82c3e7fdca5c?ixlib=rb-1.2.1&ixid=MnwxMjA3fDB8MHxzZWFyY2h8MXx8aHVtYW4lMjBmYWNlfGVufDB8fDB8fA%3D%3D&w=1000&q=80", +] +file_dir = os.path.join(os.path.dirname(__file__), "..", "kitchen_sink", "files") +model3d_dir = os.path.join(os.path.dirname(__file__), "..", "model3D", "files") +highlighted_text_output_1 = [ + { + "entity": "I-LOC", + "score": 0.9988978, + "index": 2, + "word": "Chicago", + "start": 5, + "end": 12, + }, + { + "entity": "I-MISC", + "score": 0.9958592, + "index": 5, + "word": "Pakistani", + "start": 22, + "end": 31, + }, +] +highlighted_text_output_2 = [ + { + "entity": "I-LOC", + "score": 0.9988978, + "index": 2, + "word": "Chicago", + "start": 5, + "end": 12, + }, + { + "entity": "I-LOC", + "score": 0.9958592, + "index": 5, + "word": "Pakistan", + "start": 22, + "end": 30, + }, +] + +highlighted_text = "Does Chicago have any Pakistani restaurants" + + +def random_model3d(): + model_3d = random.choice( + [os.path.join(model3d_dir, model) for model in os.listdir(model3d_dir) if model != "source.txt"] + ) + return model_3d + + + +components = [ + gr.Textbox(value=lambda: datetime.now(), label="Current Time"), + gr.Number(value=lambda: random.random(), label="Random Percentage"), + gr.Slider(minimum=0, maximum=100, randomize=True, label="Slider with randomize"), + gr.Slider( + minimum=0, + maximum=1, + value=lambda: random.random(), + label="Slider with value func", + ), + gr.Checkbox(value=lambda: random.random() > 0.5, label="Random Checkbox"), + gr.CheckboxGroup( + choices=["a", "b", "c", "d"], + value=lambda: random.choice(["a", "b", "c", "d"]), + label="Random CheckboxGroup", + ), + gr.Radio( + choices=list(string.ascii_lowercase), + value=lambda: random.choice(string.ascii_lowercase), + ), + gr.Dropdown( + choices=["a", "b", "c", "d", "e"], + value=lambda: random.choice(["a", "b", "c"]), + ), + gr.Image( + value=lambda: random.choice(images) + ), + gr.Video(value=lambda: os.path.join(file_dir, "world.mp4")), + gr.Audio(value=lambda: os.path.join(file_dir, "cantina.wav")), + gr.File( + value=lambda: random.choice( + [os.path.join(file_dir, img) for img in os.listdir(file_dir)] + ) + ), + gr.Dataframe( + value=lambda: pd.DataFrame({"random_number_rows": range(5)}, columns=["one", "two", "three"]) + ), + gr.ColorPicker(value=lambda: random.choice(["#000000", "#ff0000", "#0000FF"])), + gr.Label(value=lambda: random.choice(["Pedestrian", "Car", "Cyclist"])), + gr.HighlightedText( + value=lambda: random.choice( + [ + {"text": highlighted_text, "entities": highlighted_text_output_1}, + {"text": highlighted_text, "entities": highlighted_text_output_2}, + ] + ), + ), + gr.JSON(value=lambda: random.choice([{"a": 1}, {"b": 2}])), + gr.HTML( + value=lambda: random.choice( + [ + '

I am red

', + '

I am blue

', + ] + ) + ), + gr.Gallery( + value=lambda: images + ), + gr.Model3D(value=random_model3d), + gr.Plot(value=random_plot), + gr.Markdown(value=lambda: f"### {random.choice(['Hello', 'Hi', 'Goodbye!'])}"), +] + + +def evaluate_values(*args): + are_false = [] + for a in args: + if isinstance(a, (pd.DataFrame, np.ndarray)): + are_false.append(not a.any().any()) + elif isinstance(a, str) and a.startswith("#"): + are_false.append(a == "#000000") + else: + are_false.append(not a) + return all(are_false) + + +with gr.Blocks() as demo: + for i, component in enumerate(components): + component.label = f"component_{str(i).zfill(2)}" + component.render() + clear = gr.ClearButton(value="Clear", components=components) + result = gr.Textbox(label="Are all cleared?") + hide = gr.Button(value="Hide") + reveal = gr.Button(value="Reveal") + clear_button_and_components = components + [clear] + hide.click( + lambda: [c.__class__(visible=False) for c in clear_button_and_components], + inputs=[], + outputs=clear_button_and_components + ) + reveal.click( + lambda: [c.__class__(visible=True) for c in clear_button_and_components], + inputs=[], + outputs=clear_button_and_components + ) + get_value = gr.Button(value="Get Values") + get_value.click(evaluate_values, components, result) + + +if __name__ == "__main__": + demo.launch() diff --git a/demos/code/file.css b/demos/code/file.css new file mode 100644 index 0000000000000000000000000000000000000000..abc61b61cbb2045ad539bb1cc23c232a97aab8ee --- /dev/null +++ b/demos/code/file.css @@ -0,0 +1,11 @@ +.class { + color: blue; +} + +#id { + color: pink; +} + +div { + color: purple; +} \ No newline at end of file diff --git a/demos/code/run.ipynb b/demos/code/run.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..06f147924fcc15631e2a610b2476cfe5bfeaf9cc --- /dev/null +++ b/demos/code/run.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: code"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/code/file.css"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import os\n", "from time import sleep\n", "\n", "\n", "css_file = os.path.join(os.path.abspath(''), \"file.css\")\n", "\n", "\n", "def set_lang(language):\n", " print(language)\n", " return gr.Code(language=language)\n", "\n", "\n", "def set_lang_from_path():\n", " sleep(1)\n", " return gr.Code((css_file,), language=\"css\")\n", "\n", "\n", "def code(language, code):\n", " return gr.Code(code, language=language)\n", "\n", "\n", "io = gr.Interface(lambda x: x, \"code\", \"code\")\n", "\n", "with gr.Blocks() as demo:\n", " lang = gr.Dropdown(value=\"python\", choices=gr.Code.languages)\n", " with gr.Row():\n", " code_in = gr.Code(\n", " language=\"python\",\n", " label=\"Input\",\n", " value='def all_odd_elements(sequence):\\n \"\"\"Returns every odd element of the sequence.\"\"\"',\n", " )\n", " code_out = gr.Code(label=\"Output\")\n", " btn = gr.Button(\"Run\")\n", " btn_two = gr.Button(\"Load File\")\n", "\n", " lang.change(set_lang, inputs=lang, outputs=code_in)\n", " btn.click(code, inputs=[lang, code_in], outputs=code_out)\n", " btn_two.click(set_lang_from_path, inputs=None, outputs=code_out)\n", " io.render()\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} \ No newline at end of file diff --git a/demos/code/run.py b/demos/code/run.py new file mode 100644 index 0000000000000000000000000000000000000000..7a2aa6f1ee9bad7a6d248a5951a10821499ae7d1 --- /dev/null +++ b/demos/code/run.py @@ -0,0 +1,43 @@ +import gradio as gr +import os +from time import sleep + + +css_file = os.path.join(os.path.dirname(__file__), "file.css") + + +def set_lang(language): + print(language) + return gr.Code(language=language) + + +def set_lang_from_path(): + sleep(1) + return gr.Code((css_file,), language="css") + + +def code(language, code): + return gr.Code(code, language=language) + + +io = gr.Interface(lambda x: x, "code", "code") + +with gr.Blocks() as demo: + lang = gr.Dropdown(value="python", choices=gr.Code.languages) + with gr.Row(): + code_in = gr.Code( + language="python", + label="Input", + value='def all_odd_elements(sequence):\n """Returns every odd element of the sequence."""', + ) + code_out = gr.Code(label="Output") + btn = gr.Button("Run") + btn_two = gr.Button("Load File") + + lang.change(set_lang, inputs=lang, outputs=code_in) + btn.click(code, inputs=[lang, code_in], outputs=code_out) + btn_two.click(set_lang_from_path, inputs=None, outputs=code_out) + io.render() + +if __name__ == "__main__": + demo.launch() diff --git a/demos/fake_diffusion_with_gif/run.ipynb b/demos/fake_diffusion_with_gif/run.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..0df082ac51f379edc3945e3f7f4b9c2be7626cd4 --- /dev/null +++ b/demos/fake_diffusion_with_gif/run.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: fake_diffusion_with_gif"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import numpy as np\n", "import time\n", "import os\n", "from PIL import Image\n", "import requests\n", "from io import BytesIO\n", "\n", "\n", "def create_gif(images):\n", " pil_images = []\n", " for image in images:\n", " if isinstance(image, str):\n", " response = requests.get(image)\n", " image = Image.open(BytesIO(response.content))\n", " else:\n", " image = Image.fromarray((image * 255).astype(np.uint8))\n", " pil_images.append(image)\n", " fp_out = os.path.join(os.path.abspath(''), \"image.gif\")\n", " img = pil_images.pop(0)\n", " img.save(fp=fp_out, format='GIF', append_images=pil_images,\n", " save_all=True, duration=400, loop=0)\n", " return fp_out\n", "\n", "\n", "def fake_diffusion(steps):\n", " rng = np.random.default_rng()\n", " images = []\n", " for _ in range(steps):\n", " time.sleep(1)\n", " image = rng.random((600, 600, 3))\n", " images.append(image)\n", " yield image, gr.Image(visible=False)\n", "\n", " time.sleep(1)\n", " image = \"https://gradio-builds.s3.amazonaws.com/diffusion_image/cute_dog.jpg\"\n", " images.append(image)\n", " gif_path = create_gif(images)\n", "\n", " yield image, gr.Image(value=gif_path, visible=True)\n", "\n", "\n", "demo = gr.Interface(fake_diffusion,\n", " inputs=gr.Slider(1, 10, 3, step=1),\n", " outputs=[\"image\", gr.Image(label=\"All Images\", visible=False)])\n", "demo.queue()\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} \ No newline at end of file diff --git a/demos/fake_diffusion_with_gif/run.py b/demos/fake_diffusion_with_gif/run.py new file mode 100644 index 0000000000000000000000000000000000000000..20b87cc1c3eed8c381385cb39c45681c92854828 --- /dev/null +++ b/demos/fake_diffusion_with_gif/run.py @@ -0,0 +1,49 @@ +import gradio as gr +import numpy as np +import time +import os +from PIL import Image +import requests +from io import BytesIO + + +def create_gif(images): + pil_images = [] + for image in images: + if isinstance(image, str): + response = requests.get(image) + image = Image.open(BytesIO(response.content)) + else: + image = Image.fromarray((image * 255).astype(np.uint8)) + pil_images.append(image) + fp_out = os.path.join(os.path.dirname(__file__), "image.gif") + img = pil_images.pop(0) + img.save(fp=fp_out, format='GIF', append_images=pil_images, + save_all=True, duration=400, loop=0) + return fp_out + + +def fake_diffusion(steps): + rng = np.random.default_rng() + images = [] + for _ in range(steps): + time.sleep(1) + image = rng.random((600, 600, 3)) + images.append(image) + yield image, gr.Image(visible=False) + + time.sleep(1) + image = "https://gradio-builds.s3.amazonaws.com/diffusion_image/cute_dog.jpg" + images.append(image) + gif_path = create_gif(images) + + yield image, gr.Image(value=gif_path, visible=True) + + +demo = gr.Interface(fake_diffusion, + inputs=gr.Slider(1, 10, 3, step=1), + outputs=["image", gr.Image(label="All Images", visible=False)]) +demo.queue() + +if __name__ == "__main__": + demo.launch() diff --git a/demos/fake_gan/DESCRIPTION.md b/demos/fake_gan/DESCRIPTION.md new file mode 100644 index 0000000000000000000000000000000000000000..2eb2efc0f04eb97bb167e391ab7aa8f5dea8e3b4 --- /dev/null +++ b/demos/fake_gan/DESCRIPTION.md @@ -0,0 +1 @@ +This is a fake GAN that shows how to create a text-to-image interface for image generation. Check out the Stable Diffusion demo for more: https://hf.co/spaces/stabilityai/stable-diffusion/ \ No newline at end of file diff --git a/demos/fake_gan/run.ipynb b/demos/fake_gan/run.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..f03cfa9dbc7bbf6b214944702ccdd874002207d9 --- /dev/null +++ b/demos/fake_gan/run.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: fake_gan\n", "### This is a fake GAN that shows how to create a text-to-image interface for image generation. Check out the Stable Diffusion demo for more: https://hf.co/spaces/stabilityai/stable-diffusion/\n", " "]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["# This demo needs to be run from the repo folder.\n", "# python demo/fake_gan/run.py\n", "import random\n", "\n", "import gradio as gr\n", "\n", "\n", "def fake_gan():\n", " images = [\n", " (random.choice(\n", " [\n", " \"http://www.marketingtool.online/en/face-generator/img/faces/avatar-1151ce9f4b2043de0d2e3b7826127998.jpg\",\n", " \"http://www.marketingtool.online/en/face-generator/img/faces/avatar-116b5e92936b766b7fdfc242649337f7.jpg\",\n", " \"http://www.marketingtool.online/en/face-generator/img/faces/avatar-1163530ca19b5cebe1b002b8ec67b6fc.jpg\",\n", " \"http://www.marketingtool.online/en/face-generator/img/faces/avatar-1116395d6e6a6581eef8b8038f4c8e55.jpg\",\n", " \"http://www.marketingtool.online/en/face-generator/img/faces/avatar-11319be65db395d0e8e6855d18ddcef0.jpg\",\n", " ]\n", " ), f\"label {i}\")\n", " for i in range(3)\n", " ]\n", " return images\n", "\n", "\n", "with gr.Blocks() as demo:\n", " gallery = gr.Gallery(\n", " label=\"Generated images\", show_label=False, elem_id=\"gallery\"\n", " , columns=[3], rows=[1], object_fit=\"contain\", height=\"auto\")\n", " btn = gr.Button(\"Generate images\", scale=0)\n", "\n", " btn.click(fake_gan, None, gallery)\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} \ No newline at end of file diff --git a/demos/fake_gan/run.py b/demos/fake_gan/run.py new file mode 100644 index 0000000000000000000000000000000000000000..b3ea489cee0f42b6bc26b4809ba7c62dba54d1f6 --- /dev/null +++ b/demos/fake_gan/run.py @@ -0,0 +1,33 @@ +# This demo needs to be run from the repo folder. +# python demo/fake_gan/run.py +import random + +import gradio as gr + + +def fake_gan(): + images = [ + (random.choice( + [ + "http://www.marketingtool.online/en/face-generator/img/faces/avatar-1151ce9f4b2043de0d2e3b7826127998.jpg", + "http://www.marketingtool.online/en/face-generator/img/faces/avatar-116b5e92936b766b7fdfc242649337f7.jpg", + "http://www.marketingtool.online/en/face-generator/img/faces/avatar-1163530ca19b5cebe1b002b8ec67b6fc.jpg", + "http://www.marketingtool.online/en/face-generator/img/faces/avatar-1116395d6e6a6581eef8b8038f4c8e55.jpg", + "http://www.marketingtool.online/en/face-generator/img/faces/avatar-11319be65db395d0e8e6855d18ddcef0.jpg", + ] + ), f"label {i}") + for i in range(3) + ] + return images + + +with gr.Blocks() as demo: + gallery = gr.Gallery( + label="Generated images", show_label=False, elem_id="gallery" + , columns=[3], rows=[1], object_fit="contain", height="auto") + btn = gr.Button("Generate images", scale=0) + + btn.click(fake_gan, None, gallery) + +if __name__ == "__main__": + demo.launch() diff --git a/demos/file_explorer_component_events/dir1/bar.txt b/demos/file_explorer_component_events/dir1/bar.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/demos/file_explorer_component_events/dir1/foo.txt b/demos/file_explorer_component_events/dir1/foo.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/demos/file_explorer_component_events/dir2/baz.png b/demos/file_explorer_component_events/dir2/baz.png new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/demos/file_explorer_component_events/dir2/foo.png b/demos/file_explorer_component_events/dir2/foo.png new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/demos/file_explorer_component_events/dir3/dir3_bar.log b/demos/file_explorer_component_events/dir3/dir3_bar.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/demos/file_explorer_component_events/dir3/dir3_foo.txt b/demos/file_explorer_component_events/dir3/dir3_foo.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/demos/file_explorer_component_events/dir3/dir4/dir5/dir5_foo.txt b/demos/file_explorer_component_events/dir3/dir4/dir5/dir5_foo.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/demos/file_explorer_component_events/dir3/dir4/dir7/dir7_foo.txt b/demos/file_explorer_component_events/dir3/dir4/dir7/dir7_foo.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/demos/file_explorer_component_events/dir3/dir4/dir_4_bar.log b/demos/file_explorer_component_events/dir3/dir4/dir_4_bar.log new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/demos/file_explorer_component_events/dir3/dir4/dir_4_foo.txt b/demos/file_explorer_component_events/dir3/dir4/dir_4_foo.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/demos/file_explorer_component_events/run.ipynb b/demos/file_explorer_component_events/run.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..8dc663c498903a767fd517b5e2964aec72cd2fb3 --- /dev/null +++ b/demos/file_explorer_component_events/run.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: file_explorer_component_events"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "os.mkdir('dir1')\n", "!wget -q -O dir1/bar.txt https://github.com/gradio-app/gradio/raw/main/demo/file_explorer_component_events/dir1/bar.txt\n", "!wget -q -O dir1/foo.txt https://github.com/gradio-app/gradio/raw/main/demo/file_explorer_component_events/dir1/foo.txt\n", "os.mkdir('dir2')\n", "!wget -q -O dir2/baz.png https://github.com/gradio-app/gradio/raw/main/demo/file_explorer_component_events/dir2/baz.png\n", "!wget -q -O dir2/foo.png https://github.com/gradio-app/gradio/raw/main/demo/file_explorer_component_events/dir2/foo.png\n", "os.mkdir('dir3')\n", "!wget -q -O dir3/dir3_bar.log https://github.com/gradio-app/gradio/raw/main/demo/file_explorer_component_events/dir3/dir3_bar.log\n", "!wget -q -O dir3/dir3_foo.txt https://github.com/gradio-app/gradio/raw/main/demo/file_explorer_component_events/dir3/dir3_foo.txt\n", "!wget -q -O dir3/dir4 https://github.com/gradio-app/gradio/raw/main/demo/file_explorer_component_events/dir3/dir4"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "from pathlib import Path\n", "\n", "base_root = Path(__file__).parent.resolve()\n", "\n", "with gr.Blocks() as demo:\n", " with gr.Row():\n", " dd = gr.Dropdown(label=\"Select File Explorer Root\",\n", " value=str(base_root / \"dir1\"),\n", " choices=[str(base_root / \"dir1\"), str(base_root / \"dir2\"),\n", " str(base_root / \"dir3\")])\n", " with gr.Group():\n", " txt_only_glob = gr.Checkbox(label=\"Show only text files\", value=False)\n", " ignore_txt_in_glob = gr.Checkbox(label=\"Ignore text files in glob\", value=False)\n", "\n", " fe = gr.FileExplorer(root_dir=str(base_root / \"dir1\"),\n", " glob=\"**/*\", interactive=True)\n", " textbox = gr.Textbox(label=\"Selected Directory\")\n", " run = gr.Button(\"Run\")\n", " total_changes = gr.Number(0, elem_id=\"total-changes\")\n", " \n", " txt_only_glob.select(lambda s: gr.FileExplorer(glob=\"*.txt\" if s else \"*\") ,\n", " inputs=[txt_only_glob], outputs=[fe])\n", " ignore_txt_in_glob.select(lambda s: gr.FileExplorer(ignore_glob=\"*.txt\" if s else None),\n", " inputs=[ignore_txt_in_glob], outputs=[fe]) \n", "\n", " dd.select(lambda s: gr.FileExplorer(root=s), inputs=[dd], outputs=[fe])\n", " run.click(lambda s: \",\".join(s) if isinstance(s, list) else s, inputs=[fe], outputs=[textbox])\n", " fe.change(lambda num: num + 1, inputs=total_changes, outputs=total_changes)\n", "\n", " with gr.Row():\n", " a = gr.Textbox(elem_id=\"input-box\")\n", " a.change(lambda x: x, inputs=[a])\n", "\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} \ No newline at end of file diff --git a/demos/file_explorer_component_events/run.py b/demos/file_explorer_component_events/run.py new file mode 100644 index 0000000000000000000000000000000000000000..c991bc9e55f6c843013f63de7f317cf41e2bc75d --- /dev/null +++ b/demos/file_explorer_component_events/run.py @@ -0,0 +1,37 @@ +import gradio as gr +from pathlib import Path + +base_root = Path(__file__).parent.resolve() + +with gr.Blocks() as demo: + with gr.Row(): + dd = gr.Dropdown(label="Select File Explorer Root", + value=str(base_root / "dir1"), + choices=[str(base_root / "dir1"), str(base_root / "dir2"), + str(base_root / "dir3")]) + with gr.Group(): + txt_only_glob = gr.Checkbox(label="Show only text files", value=False) + ignore_txt_in_glob = gr.Checkbox(label="Ignore text files in glob", value=False) + + fe = gr.FileExplorer(root_dir=str(base_root / "dir1"), + glob="**/*", interactive=True) + textbox = gr.Textbox(label="Selected Directory") + run = gr.Button("Run") + total_changes = gr.Number(0, elem_id="total-changes") + + txt_only_glob.select(lambda s: gr.FileExplorer(glob="*.txt" if s else "*") , + inputs=[txt_only_glob], outputs=[fe]) + ignore_txt_in_glob.select(lambda s: gr.FileExplorer(ignore_glob="*.txt" if s else None), + inputs=[ignore_txt_in_glob], outputs=[fe]) + + dd.select(lambda s: gr.FileExplorer(root=s), inputs=[dd], outputs=[fe]) + run.click(lambda s: ",".join(s) if isinstance(s, list) else s, inputs=[fe], outputs=[textbox]) + fe.change(lambda num: num + 1, inputs=total_changes, outputs=total_changes) + + with gr.Row(): + a = gr.Textbox(elem_id="input-box") + a.change(lambda x: x, inputs=[a]) + + +if __name__ == "__main__": + demo.launch() \ No newline at end of file diff --git a/demos/image_editor_events/run.ipynb b/demos/image_editor_events/run.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..7db9c7a6de56e7fec136fd9eed31e4ff625e65e1 --- /dev/null +++ b/demos/image_editor_events/run.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: image_editor_events"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "\n", "\n", "def predict(im):\n", " return im[\"composite\"]\n", "\n", "\n", "with gr.Blocks() as demo:\n", " with gr.Group():\n", " with gr.Row():\n", " im = gr.ImageEditor(\n", " type=\"numpy\",\n", " crop_size=\"1:1\",\n", " elem_id=\"image_editor\",\n", " )\n", " im_preview = gr.Image()\n", " with gr.Group():\n", " with gr.Row():\n", "\n", " n_upload = gr.Label(\n", " 0,\n", " label=\"upload\",\n", " elem_id=\"upload\",\n", " )\n", " n_change = gr.Label(\n", " 0,\n", " label=\"change\",\n", " elem_id=\"change\",\n", " )\n", " n_input = gr.Label(\n", " 0,\n", " label=\"input\",\n", " elem_id=\"input\",\n", " )\n", " n_apply = gr.Label(\n", " 0,\n", " label=\"apply\",\n", " elem_id=\"apply\",\n", " )\n", " clear_btn = gr.Button(\"Clear\", elem_id=\"clear\")\n", "\n", " im.upload(\n", " lambda x: int(x) + 1, outputs=n_upload, inputs=n_upload, show_progress=\"hidden\"\n", " )\n", " im.change(\n", " lambda x: int(x) + 1, outputs=n_change, inputs=n_change, show_progress=\"hidden\"\n", " )\n", " im.input(\n", " lambda x: int(x) + 1, outputs=n_input, inputs=n_input, show_progress=\"hidden\"\n", " )\n", " im.apply(\n", " lambda x: int(x) + 1, outputs=n_apply, inputs=n_apply, show_progress=\"hidden\"\n", " )\n", " im.change(predict, outputs=im_preview, inputs=im, show_progress=\"hidden\")\n", " clear_btn.click(\n", " lambda: None,\n", " None,\n", " im,\n", " )\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} \ No newline at end of file diff --git a/demos/image_editor_events/run.py b/demos/image_editor_events/run.py new file mode 100644 index 0000000000000000000000000000000000000000..fb27d92ff1778c3f161ff0461e35412adf8104c7 --- /dev/null +++ b/demos/image_editor_events/run.py @@ -0,0 +1,62 @@ +import gradio as gr + + +def predict(im): + return im["composite"] + + +with gr.Blocks() as demo: + with gr.Group(): + with gr.Row(): + im = gr.ImageEditor( + type="numpy", + crop_size="1:1", + elem_id="image_editor", + ) + im_preview = gr.Image() + with gr.Group(): + with gr.Row(): + + n_upload = gr.Label( + 0, + label="upload", + elem_id="upload", + ) + n_change = gr.Label( + 0, + label="change", + elem_id="change", + ) + n_input = gr.Label( + 0, + label="input", + elem_id="input", + ) + n_apply = gr.Label( + 0, + label="apply", + elem_id="apply", + ) + clear_btn = gr.Button("Clear", elem_id="clear") + + im.upload( + lambda x: int(x) + 1, outputs=n_upload, inputs=n_upload, show_progress="hidden" + ) + im.change( + lambda x: int(x) + 1, outputs=n_change, inputs=n_change, show_progress="hidden" + ) + im.input( + lambda x: int(x) + 1, outputs=n_input, inputs=n_input, show_progress="hidden" + ) + im.apply( + lambda x: int(x) + 1, outputs=n_apply, inputs=n_apply, show_progress="hidden" + ) + im.change(predict, outputs=im_preview, inputs=im, show_progress="hidden") + clear_btn.click( + lambda: None, + None, + im, + ) + +if __name__ == "__main__": + demo.launch() diff --git a/demos/image_mod_default_image/images/cheetah1.jpg b/demos/image_mod_default_image/images/cheetah1.jpg new file mode 100644 index 0000000000000000000000000000000000000000..c510ff30e09c1ce410afa499f0bfc3a63c751134 Binary files /dev/null and b/demos/image_mod_default_image/images/cheetah1.jpg differ diff --git a/demos/image_mod_default_image/images/lion.jpg b/demos/image_mod_default_image/images/lion.jpg new file mode 100644 index 0000000000000000000000000000000000000000..e9bf9f5d0816d6201b4862088dc74476249a6a70 Binary files /dev/null and b/demos/image_mod_default_image/images/lion.jpg differ diff --git a/demos/image_mod_default_image/images/logo.png b/demos/image_mod_default_image/images/logo.png new file mode 100644 index 0000000000000000000000000000000000000000..8f1df7156f0a690a2415903061e19c20e24adac4 Binary files /dev/null and b/demos/image_mod_default_image/images/logo.png differ diff --git a/demos/image_mod_default_image/run.ipynb b/demos/image_mod_default_image/run.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..1a17252385a81c5a64a62d2b4dc61b5969dbbc7f --- /dev/null +++ b/demos/image_mod_default_image/run.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: image_mod_default_image"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "os.mkdir('images')\n", "!wget -q -O images/cheetah1.jpg https://github.com/gradio-app/gradio/raw/main/demo/image_mod_default_image/images/cheetah1.jpg\n", "!wget -q -O images/lion.jpg https://github.com/gradio-app/gradio/raw/main/demo/image_mod_default_image/images/lion.jpg\n", "!wget -q -O images/logo.png https://github.com/gradio-app/gradio/raw/main/demo/image_mod_default_image/images/logo.png"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import os\n", "\n", "\n", "def image_mod(image):\n", " return image.rotate(45)\n", "\n", "\n", "cheetah = os.path.join(os.path.abspath(''), \"images/cheetah1.jpg\")\n", "\n", "demo = gr.Interface(image_mod, gr.Image(type=\"pil\", value=cheetah), \"image\",\n", " flagging_options=[\"blurry\", \"incorrect\", \"other\"], examples=[\n", " os.path.join(os.path.abspath(''), \"images/lion.jpg\"),\n", " os.path.join(os.path.abspath(''), \"images/logo.png\")\n", " ])\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch(max_file_size=\"70kb\")\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} \ No newline at end of file diff --git a/demos/image_mod_default_image/run.py b/demos/image_mod_default_image/run.py new file mode 100644 index 0000000000000000000000000000000000000000..d05c3e299b27c2331fc8e6f8a17fc34afd904adb --- /dev/null +++ b/demos/image_mod_default_image/run.py @@ -0,0 +1,18 @@ +import gradio as gr +import os + + +def image_mod(image): + return image.rotate(45) + + +cheetah = os.path.join(os.path.dirname(__file__), "images/cheetah1.jpg") + +demo = gr.Interface(image_mod, gr.Image(type="pil", value=cheetah), "image", + flagging_options=["blurry", "incorrect", "other"], examples=[ + os.path.join(os.path.dirname(__file__), "images/lion.jpg"), + os.path.join(os.path.dirname(__file__), "images/logo.png") + ]) + +if __name__ == "__main__": + demo.launch(max_file_size="70kb") diff --git a/demos/image_segmentation/DESCRIPTION.md b/demos/image_segmentation/DESCRIPTION.md new file mode 100644 index 0000000000000000000000000000000000000000..dbba2ae29e4ed391bfd1681fb2fe7d0efcb34222 --- /dev/null +++ b/demos/image_segmentation/DESCRIPTION.md @@ -0,0 +1 @@ +Simple image segmentation using gradio's AnnotatedImage component. \ No newline at end of file diff --git a/demos/image_segmentation/run.ipynb b/demos/image_segmentation/run.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..ac39c2862e509bcadc97ace2367edf2a8672e98e --- /dev/null +++ b/demos/image_segmentation/run.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: image_segmentation\n", "### Simple image segmentation using gradio's AnnotatedImage component.\n", " "]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import numpy as np\n", "import random\n", "\n", "with gr.Blocks() as demo:\n", " section_labels = [\n", " \"apple\",\n", " \"banana\",\n", " \"carrot\",\n", " \"donut\",\n", " \"eggplant\",\n", " \"fish\",\n", " \"grapes\",\n", " \"hamburger\",\n", " \"ice cream\",\n", " \"juice\",\n", " ]\n", "\n", " with gr.Row():\n", " num_boxes = gr.Slider(0, 5, 2, step=1, label=\"Number of boxes\")\n", " num_segments = gr.Slider(0, 5, 1, step=1, label=\"Number of segments\")\n", "\n", " with gr.Row():\n", " img_input = gr.Image()\n", " img_output = gr.AnnotatedImage(\n", " color_map={\"banana\": \"#a89a00\", \"carrot\": \"#ffae00\"}\n", " )\n", "\n", " section_btn = gr.Button(\"Identify Sections\")\n", " selected_section = gr.Textbox(label=\"Selected Section\")\n", "\n", " def section(img, num_boxes, num_segments):\n", " sections = []\n", " for a in range(num_boxes):\n", " x = random.randint(0, img.shape[1])\n", " y = random.randint(0, img.shape[0])\n", " w = random.randint(0, img.shape[1] - x)\n", " h = random.randint(0, img.shape[0] - y)\n", " sections.append(((x, y, x + w, y + h), section_labels[a]))\n", " for b in range(num_segments):\n", " x = random.randint(0, img.shape[1])\n", " y = random.randint(0, img.shape[0])\n", " r = random.randint(0, min(x, y, img.shape[1] - x, img.shape[0] - y))\n", " mask = np.zeros(img.shape[:2])\n", " for i in range(img.shape[0]):\n", " for j in range(img.shape[1]):\n", " dist_square = (i - y) ** 2 + (j - x) ** 2\n", " if dist_square < r**2:\n", " mask[i, j] = round((r**2 - dist_square) / r**2 * 4) / 4\n", " sections.append((mask, section_labels[b + num_boxes]))\n", " return (img, sections)\n", "\n", " section_btn.click(section, [img_input, num_boxes, num_segments], img_output)\n", "\n", " def select_section(evt: gr.SelectData):\n", " return section_labels[evt.index]\n", "\n", " img_output.select(select_section, None, selected_section)\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} \ No newline at end of file diff --git a/demos/image_segmentation/run.py b/demos/image_segmentation/run.py new file mode 100644 index 0000000000000000000000000000000000000000..af3793f3217683102683eeb9a559bdff92a57066 --- /dev/null +++ b/demos/image_segmentation/run.py @@ -0,0 +1,61 @@ +import gradio as gr +import numpy as np +import random + +with gr.Blocks() as demo: + section_labels = [ + "apple", + "banana", + "carrot", + "donut", + "eggplant", + "fish", + "grapes", + "hamburger", + "ice cream", + "juice", + ] + + with gr.Row(): + num_boxes = gr.Slider(0, 5, 2, step=1, label="Number of boxes") + num_segments = gr.Slider(0, 5, 1, step=1, label="Number of segments") + + with gr.Row(): + img_input = gr.Image() + img_output = gr.AnnotatedImage( + color_map={"banana": "#a89a00", "carrot": "#ffae00"} + ) + + section_btn = gr.Button("Identify Sections") + selected_section = gr.Textbox(label="Selected Section") + + def section(img, num_boxes, num_segments): + sections = [] + for a in range(num_boxes): + x = random.randint(0, img.shape[1]) + y = random.randint(0, img.shape[0]) + w = random.randint(0, img.shape[1] - x) + h = random.randint(0, img.shape[0] - y) + sections.append(((x, y, x + w, y + h), section_labels[a])) + for b in range(num_segments): + x = random.randint(0, img.shape[1]) + y = random.randint(0, img.shape[0]) + r = random.randint(0, min(x, y, img.shape[1] - x, img.shape[0] - y)) + mask = np.zeros(img.shape[:2]) + for i in range(img.shape[0]): + for j in range(img.shape[1]): + dist_square = (i - y) ** 2 + (j - x) ** 2 + if dist_square < r**2: + mask[i, j] = round((r**2 - dist_square) / r**2 * 4) / 4 + sections.append((mask, section_labels[b + num_boxes])) + return (img, sections) + + section_btn.click(section, [img_input, num_boxes, num_segments], img_output) + + def select_section(evt: gr.SelectData): + return section_labels[evt.index] + + img_output.select(select_section, None, selected_section) + +if __name__ == "__main__": + demo.launch() diff --git a/demos/interface_random_slider/run.ipynb b/demos/interface_random_slider/run.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..dcdef26f3983bbd6d3a66fdbe9392d209ed20cc8 --- /dev/null +++ b/demos/interface_random_slider/run.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: interface_random_slider"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "\n", "\n", "def func(slider_1, slider_2, *args):\n", " return slider_1 + slider_2 * 5\n", "\n", "\n", "demo = gr.Interface(\n", " func,\n", " [\n", " gr.Slider(minimum=1.5, maximum=250000.89, randomize=True, label=\"Random Big Range\"),\n", " gr.Slider(minimum=-1, maximum=1, randomize=True, step=0.05, label=\"Random only multiple of 0.05 allowed\"),\n", " gr.Slider(minimum=0, maximum=1, randomize=True, step=0.25, label=\"Random only multiples of 0.25 allowed\"),\n", " gr.Slider(minimum=-100, maximum=100, randomize=True, step=3, label=\"Random between -100 and 100 step 3\"),\n", " gr.Slider(minimum=-100, maximum=100, randomize=True, label=\"Random between -100 and 100\"),\n", " gr.Slider(value=0.25, minimum=5, maximum=30, step=-1),\n", " ],\n", " \"number\",\n", ")\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} \ No newline at end of file diff --git a/demos/interface_random_slider/run.py b/demos/interface_random_slider/run.py new file mode 100644 index 0000000000000000000000000000000000000000..5d199f706615434773b48cbd1c7f6fcb199eba0f --- /dev/null +++ b/demos/interface_random_slider/run.py @@ -0,0 +1,22 @@ +import gradio as gr + + +def func(slider_1, slider_2, *args): + return slider_1 + slider_2 * 5 + + +demo = gr.Interface( + func, + [ + gr.Slider(minimum=1.5, maximum=250000.89, randomize=True, label="Random Big Range"), + gr.Slider(minimum=-1, maximum=1, randomize=True, step=0.05, label="Random only multiple of 0.05 allowed"), + gr.Slider(minimum=0, maximum=1, randomize=True, step=0.25, label="Random only multiples of 0.25 allowed"), + gr.Slider(minimum=-100, maximum=100, randomize=True, step=3, label="Random between -100 and 100 step 3"), + gr.Slider(minimum=-100, maximum=100, randomize=True, label="Random between -100 and 100"), + gr.Slider(value=0.25, minimum=5, maximum=30, step=-1), + ], + "number", +) + +if __name__ == "__main__": + demo.launch() diff --git a/demos/kitchen_sink/files/cantina.wav b/demos/kitchen_sink/files/cantina.wav new file mode 100644 index 0000000000000000000000000000000000000000..41f020438468229763ec4a2321325e5916e09106 Binary files /dev/null and b/demos/kitchen_sink/files/cantina.wav differ diff --git a/demos/kitchen_sink/files/cheetah1.jpg b/demos/kitchen_sink/files/cheetah1.jpg new file mode 100644 index 0000000000000000000000000000000000000000..c510ff30e09c1ce410afa499f0bfc3a63c751134 Binary files /dev/null and b/demos/kitchen_sink/files/cheetah1.jpg differ diff --git a/demos/kitchen_sink/files/lion.jpg b/demos/kitchen_sink/files/lion.jpg new file mode 100644 index 0000000000000000000000000000000000000000..e9bf9f5d0816d6201b4862088dc74476249a6a70 Binary files /dev/null and b/demos/kitchen_sink/files/lion.jpg differ diff --git a/demos/kitchen_sink/files/logo.png b/demos/kitchen_sink/files/logo.png new file mode 100644 index 0000000000000000000000000000000000000000..8f1df7156f0a690a2415903061e19c20e24adac4 Binary files /dev/null and b/demos/kitchen_sink/files/logo.png differ diff --git a/demos/kitchen_sink/files/time.csv b/demos/kitchen_sink/files/time.csv new file mode 100644 index 0000000000000000000000000000000000000000..ddb2035c4ed0377f54ee1602fff9f05ba5daa2db --- /dev/null +++ b/demos/kitchen_sink/files/time.csv @@ -0,0 +1,8 @@ +time,value,price +1,1,4 +2,3,8 +3,6,12 +4,10,16 +5,15,20 +6,21,24 +7,28,28 \ No newline at end of file diff --git a/demos/kitchen_sink/files/titanic.csv b/demos/kitchen_sink/files/titanic.csv new file mode 100644 index 0000000000000000000000000000000000000000..63b68ab0ba98c667f515c52f08c0bbd5573d5330 --- /dev/null +++ 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0000000000000000000000000000000000000000..21dcacd1e6eb588b55dac8385864399eb9f72f03 --- /dev/null +++ b/demos/kitchen_sink/run.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: kitchen_sink"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "os.mkdir('files')\n", "!wget -q -O files/cantina.wav https://github.com/gradio-app/gradio/raw/main/demo/kitchen_sink/files/cantina.wav\n", "!wget -q -O files/cheetah1.jpg https://github.com/gradio-app/gradio/raw/main/demo/kitchen_sink/files/cheetah1.jpg\n", "!wget -q -O files/lion.jpg https://github.com/gradio-app/gradio/raw/main/demo/kitchen_sink/files/lion.jpg\n", "!wget -q -O files/logo.png https://github.com/gradio-app/gradio/raw/main/demo/kitchen_sink/files/logo.png\n", "!wget -q -O files/time.csv https://github.com/gradio-app/gradio/raw/main/demo/kitchen_sink/files/time.csv\n", "!wget -q -O files/titanic.csv https://github.com/gradio-app/gradio/raw/main/demo/kitchen_sink/files/titanic.csv\n", "!wget -q -O files/tower.jpg https://github.com/gradio-app/gradio/raw/main/demo/kitchen_sink/files/tower.jpg\n", "!wget -q -O files/world.mp4 https://github.com/gradio-app/gradio/raw/main/demo/kitchen_sink/files/world.mp4"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import os\n", "import json\n", "\n", "import numpy as np\n", "\n", "import gradio as gr\n", "\n", "CHOICES = [\"foo\", \"bar\", \"baz\"]\n", "JSONOBJ = \"\"\"{\"items\":{\"item\":[{\"id\": \"0001\",\"type\": null,\"is_good\": false,\"ppu\": 0.55,\"batters\":{\"batter\":[{ \"id\": \"1001\", \"type\": \"Regular\" },{ \"id\": \"1002\", \"type\": \"Chocolate\" },{ \"id\": \"1003\", \"type\": \"Blueberry\" },{ \"id\": \"1004\", \"type\": \"Devil's Food\" }]},\"topping\":[{ \"id\": \"5001\", \"type\": \"None\" },{ \"id\": \"5002\", \"type\": \"Glazed\" },{ \"id\": \"5005\", \"type\": \"Sugar\" },{ \"id\": \"5007\", \"type\": \"Powdered Sugar\" },{ \"id\": \"5006\", \"type\": \"Chocolate with Sprinkles\" },{ \"id\": \"5003\", \"type\": \"Chocolate\" },{ \"id\": \"5004\", \"type\": \"Maple\" }]}]}}\"\"\"\n", "\n", "\n", "def fn(\n", " text1,\n", " text2,\n", " num,\n", " slider1,\n", " slider2,\n", " single_checkbox,\n", " checkboxes,\n", " radio,\n", " dropdown,\n", " multi_dropdown,\n", " im1,\n", " # im2,\n", " # im3,\n", " im4,\n", " video,\n", " audio1,\n", " audio2,\n", " file,\n", " df1,\n", "):\n", " return (\n", " (text1 if single_checkbox else text2)\n", " + \", selected:\"\n", " + \", \".join(checkboxes), # Text\n", " {\n", " \"positive\": num / (num + slider1 + slider2),\n", " \"negative\": slider1 / (num + slider1 + slider2),\n", " \"neutral\": slider2 / (num + slider1 + slider2),\n", " }, # Label\n", " (audio1[0], np.flipud(audio1[1]))\n", " if audio1 is not None\n", " else os.path.join(os.path.abspath(''), \"files/cantina.wav\"), # Audio\n", " np.flipud(im1)\n", " if im1 is not None\n", " else os.path.join(os.path.abspath(''), \"files/cheetah1.jpg\"), # Image\n", " video\n", " if video is not None\n", " else os.path.join(os.path.abspath(''), \"files/world.mp4\"), # Video\n", " [\n", " (\"The\", \"art\"),\n", " (\"quick brown\", \"adj\"),\n", " (\"fox\", \"nn\"),\n", " (\"jumped\", \"vrb\"),\n", " (\"testing testing testing\", None),\n", " (\"over\", \"prp\"),\n", " (\"the\", \"art\"),\n", " (\"testing\", None),\n", " (\"lazy\", \"adj\"),\n", " (\"dogs\", \"nn\"),\n", " (\".\", \"punc\"),\n", " ]\n", " + [(f\"test {x}\", f\"test {x}\") for x in range(10)], # HighlightedText\n", " # [(\"The testing testing testing\", None), (\"quick brown\", 0.2), (\"fox\", 1), (\"jumped\", -1), (\"testing testing testing\", 0), (\"over\", 0), (\"the\", 0), (\"testing\", 0), (\"lazy\", 1), (\"dogs\", 0), (\".\", 1)] + [(f\"test {x}\", x/10) for x in range(-10, 10)], # HighlightedText\n", " [\n", " (\"The testing testing testing\", None),\n", " (\"over\", 0.6),\n", " (\"the\", 0.2),\n", " (\"testing\", None),\n", " (\"lazy\", -0.1),\n", " (\"dogs\", 0.4),\n", " (\".\", 0),\n", " ]\n", " + [(f\"test\", x / 10) for x in range(-10, 10)], # HighlightedText\n", " json.loads(JSONOBJ), # JSON\n", " \"\", # HTML\n", " os.path.join(os.path.abspath(''), \"files/titanic.csv\"),\n", " df1, # Dataframe\n", " np.random.randint(0, 10, (4, 4)), # Dataframe\n", " )\n", "\n", "\n", "demo = gr.Interface(\n", " fn,\n", " inputs=[\n", " gr.Textbox(value=\"Lorem ipsum\", label=\"Textbox\"),\n", " gr.Textbox(lines=3, placeholder=\"Type here..\", label=\"Textbox 2\"),\n", " gr.Number(label=\"Number\", value=42),\n", " gr.Slider(10, 20, value=15, label=\"Slider: 10 - 20\"),\n", " gr.Slider(maximum=20, step=0.04, label=\"Slider: step @ 0.04\"),\n", " gr.Checkbox(label=\"Checkbox\"),\n", " gr.CheckboxGroup(label=\"CheckboxGroup\", choices=CHOICES, value=CHOICES[0:2]),\n", " gr.Radio(label=\"Radio\", choices=CHOICES, value=CHOICES[2]),\n", " gr.Dropdown(label=\"Dropdown\", choices=CHOICES),\n", " gr.Dropdown(\n", " label=\"Multiselect Dropdown (Max choice: 2)\",\n", " choices=CHOICES,\n", " multiselect=True,\n", " max_choices=2,\n", " ),\n", " gr.Image(label=\"Image\"),\n", " # gr.Image(label=\"Image w/ Cropper\", tool=\"select\"),\n", " # gr.Image(label=\"Sketchpad\", source=\"canvas\"),\n", " gr.Image(label=\"Webcam\", sources=[\"webcam\"]),\n", " gr.Video(label=\"Video\"),\n", " gr.Audio(label=\"Audio\"),\n", " gr.Audio(label=\"Microphone\", sources=[\"microphone\"]),\n", " gr.File(label=\"File\"),\n", " gr.Dataframe(label=\"Dataframe\", headers=[\"Name\", \"Age\", \"Gender\"]),\n", " ],\n", " outputs=[\n", " gr.Textbox(label=\"Textbox\"),\n", " gr.Label(label=\"Label\"),\n", " gr.Audio(label=\"Audio\"),\n", " gr.Image(label=\"Image\"),\n", " gr.Video(label=\"Video\"),\n", " gr.HighlightedText(\n", " label=\"HighlightedText\", color_map={\"punc\": \"pink\", \"test 0\": \"blue\"}\n", " ),\n", " gr.HighlightedText(label=\"HighlightedText\", show_legend=True),\n", " gr.JSON(label=\"JSON\"),\n", " gr.HTML(label=\"HTML\"),\n", " gr.File(label=\"File\"),\n", " gr.Dataframe(label=\"Dataframe\"),\n", " gr.Dataframe(label=\"Numpy\"),\n", " ],\n", " examples=[\n", " [\n", " \"the quick brown fox\",\n", " \"jumps over the lazy dog\",\n", " 10,\n", " 12,\n", " 4,\n", " True,\n", " [\"foo\", \"baz\"],\n", " \"baz\",\n", " \"bar\",\n", " [\"foo\", \"bar\"],\n", " os.path.join(os.path.abspath(''), \"files/cheetah1.jpg\"),\n", " # os.path.join(os.path.abspath(''), \"files/cheetah1.jpg\"),\n", " # os.path.join(os.path.abspath(''), \"files/cheetah1.jpg\"),\n", " os.path.join(os.path.abspath(''), \"files/cheetah1.jpg\"),\n", " os.path.join(os.path.abspath(''), \"files/world.mp4\"),\n", " os.path.join(os.path.abspath(''), \"files/cantina.wav\"),\n", " os.path.join(os.path.abspath(''), \"files/cantina.wav\"),\n", " os.path.join(os.path.abspath(''), \"files/titanic.csv\"),\n", " [[1, 2, 3, 4], [4, 5, 6, 7], [8, 9, 1, 2], [3, 4, 5, 6]],\n", " ]\n", " ]\n", " * 3,\n", " title=\"Kitchen Sink\",\n", " description=\"Try out all the components!\",\n", " article=\"Learn more about [Gradio](http://gradio.app)\",\n", " cache_examples=True,\n", ")\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} \ No newline at end of file diff --git a/demos/kitchen_sink/run.py b/demos/kitchen_sink/run.py new file mode 100644 index 0000000000000000000000000000000000000000..8b21991baff3d17e7341b895862c321e239c0460 --- /dev/null +++ b/demos/kitchen_sink/run.py @@ -0,0 +1,161 @@ +import os +import json + +import numpy as np + +import gradio as gr + +CHOICES = ["foo", "bar", "baz"] +JSONOBJ = """{"items":{"item":[{"id": "0001","type": null,"is_good": false,"ppu": 0.55,"batters":{"batter":[{ "id": "1001", "type": "Regular" },{ "id": "1002", "type": "Chocolate" },{ "id": "1003", "type": "Blueberry" },{ "id": "1004", "type": "Devil's Food" }]},"topping":[{ "id": "5001", "type": "None" },{ "id": "5002", "type": "Glazed" },{ "id": "5005", "type": "Sugar" },{ "id": "5007", "type": "Powdered Sugar" },{ "id": "5006", "type": "Chocolate with Sprinkles" },{ "id": "5003", "type": "Chocolate" },{ "id": "5004", "type": "Maple" }]}]}}""" + + +def fn( + text1, + text2, + num, + slider1, + slider2, + single_checkbox, + checkboxes, + radio, + dropdown, + multi_dropdown, + im1, + # im2, + # im3, + im4, + video, + audio1, + audio2, + file, + df1, +): + return ( + (text1 if single_checkbox else text2) + + ", selected:" + + ", ".join(checkboxes), # Text + { + "positive": num / (num + slider1 + slider2), + "negative": slider1 / (num + slider1 + slider2), + "neutral": slider2 / (num + slider1 + slider2), + }, # Label + (audio1[0], np.flipud(audio1[1])) + if audio1 is not None + else os.path.join(os.path.dirname(__file__), "files/cantina.wav"), # Audio + np.flipud(im1) + if im1 is not None + else os.path.join(os.path.dirname(__file__), "files/cheetah1.jpg"), # Image + video + if video is not None + else os.path.join(os.path.dirname(__file__), "files/world.mp4"), # Video + [ + ("The", "art"), + ("quick brown", "adj"), + ("fox", "nn"), + ("jumped", "vrb"), + ("testing testing testing", None), + ("over", "prp"), + ("the", "art"), + ("testing", None), + ("lazy", "adj"), + ("dogs", "nn"), + (".", "punc"), + ] + + [(f"test {x}", f"test {x}") for x in range(10)], # HighlightedText + # [("The testing testing testing", None), ("quick brown", 0.2), ("fox", 1), ("jumped", -1), ("testing testing testing", 0), ("over", 0), ("the", 0), ("testing", 0), ("lazy", 1), ("dogs", 0), (".", 1)] + [(f"test {x}", x/10) for x in range(-10, 10)], # HighlightedText + [ + ("The testing testing testing", None), + ("over", 0.6), + ("the", 0.2), + ("testing", None), + ("lazy", -0.1), + ("dogs", 0.4), + (".", 0), + ] + + [(f"test", x / 10) for x in range(-10, 10)], # HighlightedText + json.loads(JSONOBJ), # JSON + "", # HTML + os.path.join(os.path.dirname(__file__), "files/titanic.csv"), + df1, # Dataframe + np.random.randint(0, 10, (4, 4)), # Dataframe + ) + + +demo = gr.Interface( + fn, + inputs=[ + gr.Textbox(value="Lorem ipsum", label="Textbox"), + gr.Textbox(lines=3, placeholder="Type here..", label="Textbox 2"), + gr.Number(label="Number", value=42), + gr.Slider(10, 20, value=15, label="Slider: 10 - 20"), + gr.Slider(maximum=20, step=0.04, label="Slider: step @ 0.04"), + gr.Checkbox(label="Checkbox"), + gr.CheckboxGroup(label="CheckboxGroup", choices=CHOICES, value=CHOICES[0:2]), + gr.Radio(label="Radio", choices=CHOICES, value=CHOICES[2]), + gr.Dropdown(label="Dropdown", choices=CHOICES), + gr.Dropdown( + label="Multiselect Dropdown (Max choice: 2)", + choices=CHOICES, + multiselect=True, + max_choices=2, + ), + gr.Image(label="Image"), + # gr.Image(label="Image w/ Cropper", tool="select"), + # gr.Image(label="Sketchpad", source="canvas"), + gr.Image(label="Webcam", sources=["webcam"]), + gr.Video(label="Video"), + gr.Audio(label="Audio"), + gr.Audio(label="Microphone", sources=["microphone"]), + gr.File(label="File"), + gr.Dataframe(label="Dataframe", headers=["Name", "Age", "Gender"]), + ], + outputs=[ + gr.Textbox(label="Textbox"), + gr.Label(label="Label"), + gr.Audio(label="Audio"), + gr.Image(label="Image"), + gr.Video(label="Video"), + gr.HighlightedText( + label="HighlightedText", color_map={"punc": "pink", "test 0": "blue"} + ), + gr.HighlightedText(label="HighlightedText", show_legend=True), + gr.JSON(label="JSON"), + gr.HTML(label="HTML"), + gr.File(label="File"), + gr.Dataframe(label="Dataframe"), + gr.Dataframe(label="Numpy"), + ], + examples=[ + [ + "the quick brown fox", + "jumps over the lazy dog", + 10, + 12, + 4, + True, + ["foo", "baz"], + "baz", + "bar", + ["foo", "bar"], + os.path.join(os.path.dirname(__file__), "files/cheetah1.jpg"), + # os.path.join(os.path.dirname(__file__), "files/cheetah1.jpg"), + # os.path.join(os.path.dirname(__file__), "files/cheetah1.jpg"), + os.path.join(os.path.dirname(__file__), "files/cheetah1.jpg"), + os.path.join(os.path.dirname(__file__), "files/world.mp4"), + os.path.join(os.path.dirname(__file__), "files/cantina.wav"), + os.path.join(os.path.dirname(__file__), "files/cantina.wav"), + os.path.join(os.path.dirname(__file__), "files/titanic.csv"), + [[1, 2, 3, 4], [4, 5, 6, 7], [8, 9, 1, 2], [3, 4, 5, 6]], + ] + ] + * 3, + title="Kitchen Sink", + description="Try out all the components!", + article="Learn more about [Gradio](http://gradio.app)", + cache_examples=True, +) + +if __name__ == "__main__": + demo.launch() diff --git a/demos/kitchen_sink_random/__init__.py b/demos/kitchen_sink_random/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/demos/kitchen_sink_random/constants.py b/demos/kitchen_sink_random/constants.py new file mode 100644 index 0000000000000000000000000000000000000000..bda41f4f76c8a3749a3ad970f9956d92c5e123b3 --- /dev/null +++ b/demos/kitchen_sink_random/constants.py @@ -0,0 +1,68 @@ +import numpy as np +import matplotlib.pyplot as plt +import random +import os + + +def random_plot(): + start_year = 2020 + x = np.arange(start_year, start_year + random.randint(0, 10)) + year_count = x.shape[0] + plt_format = "-" + fig = plt.figure() + ax = fig.add_subplot(111) + series = np.arange(0, year_count, dtype=float) + series = series**2 + series += np.random.rand(year_count) + ax.plot(x, series, plt_format) + return fig + + +img_dir = os.path.join(os.path.dirname(__file__), "files") +file_dir = os.path.join(os.path.dirname(__file__), "..", "kitchen_sink", "files") +model3d_dir = os.path.join(os.path.dirname(__file__), "..", "model3D", "files") +highlighted_text_output_1 = [ + { + "entity": "I-LOC", + "score": 0.9988978, + "index": 2, + "word": "Chicago", + "start": 5, + "end": 12, + }, + { + "entity": "I-MISC", + "score": 0.9958592, + "index": 5, + "word": "Pakistani", + "start": 22, + "end": 31, + }, +] +highlighted_text_output_2 = [ + { + "entity": "I-LOC", + "score": 0.9988978, + "index": 2, + "word": "Chicago", + "start": 5, + "end": 12, + }, + { + "entity": "I-LOC", + "score": 0.9958592, + "index": 5, + "word": "Pakistan", + "start": 22, + "end": 30, + }, +] + +highlighted_text = "Does Chicago have any Pakistani restaurants" + + +def random_model3d(): + model_3d = random.choice( + [os.path.join(model3d_dir, model) for model in os.listdir(model3d_dir) if model != "source.txt"] + ) + return model_3d diff --git a/demos/kitchen_sink_random/files/cheetah1.jpeg b/demos/kitchen_sink_random/files/cheetah1.jpeg new file mode 100644 index 0000000000000000000000000000000000000000..c510ff30e09c1ce410afa499f0bfc3a63c751134 Binary files /dev/null and b/demos/kitchen_sink_random/files/cheetah1.jpeg differ diff --git a/demos/kitchen_sink_random/files/cheetah1.jpg b/demos/kitchen_sink_random/files/cheetah1.jpg new file mode 100644 index 0000000000000000000000000000000000000000..c510ff30e09c1ce410afa499f0bfc3a63c751134 Binary files /dev/null and b/demos/kitchen_sink_random/files/cheetah1.jpg differ diff --git a/demos/kitchen_sink_random/files/lion.jpg b/demos/kitchen_sink_random/files/lion.jpg new file mode 100644 index 0000000000000000000000000000000000000000..e9bf9f5d0816d6201b4862088dc74476249a6a70 Binary files /dev/null and b/demos/kitchen_sink_random/files/lion.jpg differ diff --git a/demos/kitchen_sink_random/run.py b/demos/kitchen_sink_random/run.py new file mode 100644 index 0000000000000000000000000000000000000000..5b4440e94984b8da2d46b6984a78b4f663847165 --- /dev/null +++ b/demos/kitchen_sink_random/run.py @@ -0,0 +1,98 @@ +import gradio as gr +from datetime import datetime +import random +import string +import os +import pandas as pd + +from constants import ( + file_dir, + img_dir, + highlighted_text, + highlighted_text_output_2, + highlighted_text_output_1, + random_plot, + random_model3d, +) + + +demo = gr.Interface( + lambda *args: args[0], + inputs=[ + gr.Textbox(value=lambda: datetime.now(), label="Current Time"), + gr.Number(value=lambda: random.random(), label="Ranom Percentage"), + gr.Slider(minimum=-1, maximum=1, randomize=True, label="Slider with randomize"), + gr.Slider( + minimum=0, + maximum=1, + value=lambda: random.random(), + label="Slider with value func", + ), + gr.Checkbox(value=lambda: random.random() > 0.5, label="Random Checkbox"), + gr.CheckboxGroup( + choices=["a", "b", "c", "d"], + value=lambda: random.choice(["a", "b", "c", "d"]), + label="Random CheckboxGroup", + ), + gr.Radio( + choices=list(string.ascii_lowercase), + value=lambda: random.choice(string.ascii_lowercase), + ), + gr.Dropdown( + choices=["a", "b", "c", "d", "e"], + value=lambda: random.choice(["a", "b", "c"]), + ), + gr.Image( + value=lambda: random.choice( + [os.path.join(img_dir, img) for img in os.listdir(img_dir)] + ) + ), + gr.Video(value=lambda: os.path.join(file_dir, "world.mp4")), + gr.Audio(value=lambda: os.path.join(file_dir, "cantina.wav")), + gr.File( + value=lambda: random.choice( + [os.path.join(file_dir, img) for img in os.listdir(file_dir)] + ) + ), + gr.Dataframe( + value=lambda: pd.DataFrame( + {"random_number_rows": range(random.randint(0, 10))} + ) + ), + gr.State(value=lambda: random.choice(string.ascii_lowercase)), + gr.ColorPicker(value=lambda: random.choice(["#000000", "#ff0000", "#0000FF"])), + gr.Label(value=lambda: random.choice(["Pedestrian", "Car", "Cyclist"])), + gr.HighlightedText( + value=lambda: random.choice( + [ + {"text": highlighted_text, "entities": highlighted_text_output_1}, + {"text": highlighted_text, "entities": highlighted_text_output_2}, + ] + ), + ), + gr.JSON(value=lambda: random.choice([{"a": 1}, {"b": 2}])), + gr.HTML( + value=lambda: random.choice( + [ + '

I am red

', + '

I am blue

', + ] + ) + ), + gr.Gallery( + value=lambda: [os.path.join(img_dir, img) for img in os.listdir(img_dir)] + ), + gr.Chatbot( + value=lambda: random.choice([[("hello", "hi!")], [("bye", "goodbye!")]]) + ), + gr.Model3D(value=random_model3d), + gr.Plot(value=random_plot), + gr.Markdown(value=lambda: f"### {random.choice(['Hello', 'Hi', 'Goodbye!'])}"), + ], + outputs=[ + gr.State(value=lambda: random.choice(string.ascii_lowercase)) + ], +) + +if __name__ == "__main__": + demo.launch() diff --git a/demos/matrix_transpose/run.ipynb b/demos/matrix_transpose/run.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..d2d497ef82776db4deca3ad4e30bfb805226150f --- /dev/null +++ b/demos/matrix_transpose/run.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: matrix_transpose"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import numpy as np\n", "\n", "import gradio as gr\n", "\n", "\n", "def transpose(matrix):\n", " return matrix.T\n", "\n", "\n", "demo = gr.Interface(\n", " transpose,\n", " gr.Dataframe(type=\"numpy\", datatype=\"number\", row_count=5, col_count=3),\n", " \"numpy\",\n", " examples=[\n", " [np.zeros((3, 3)).tolist()],\n", " [np.ones((2, 2)).tolist()],\n", " [np.random.randint(0, 10, (3, 10)).tolist()],\n", " [np.random.randint(0, 10, (10, 3)).tolist()],\n", " [np.random.randint(0, 10, (10, 10)).tolist()],\n", " ],\n", " cache_examples=False\n", ")\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} \ No newline at end of file diff --git a/demos/matrix_transpose/run.py b/demos/matrix_transpose/run.py new file mode 100644 index 0000000000000000000000000000000000000000..34548199576ef86fa50139cbc6762e038e9d69a8 --- /dev/null +++ b/demos/matrix_transpose/run.py @@ -0,0 +1,25 @@ +import numpy as np + +import gradio as gr + + +def transpose(matrix): + return matrix.T + + +demo = gr.Interface( + transpose, + gr.Dataframe(type="numpy", datatype="number", row_count=5, col_count=3), + "numpy", + examples=[ + [np.zeros((3, 3)).tolist()], + [np.ones((2, 2)).tolist()], + [np.random.randint(0, 10, (3, 10)).tolist()], + [np.random.randint(0, 10, (10, 3)).tolist()], + [np.random.randint(0, 10, (10, 10)).tolist()], + ], + cache_examples=False +) + +if __name__ == "__main__": + demo.launch() diff --git a/demos/matrix_transpose/screenshot.png b/demos/matrix_transpose/screenshot.png new file mode 100644 index 0000000000000000000000000000000000000000..a9434e9c1df2828ecc1df700eeaaad9609109f82 Binary files /dev/null and b/demos/matrix_transpose/screenshot.png differ diff --git a/demos/mini_leaderboard/assets/__init__.py b/demos/mini_leaderboard/assets/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/demos/mini_leaderboard/assets/custom_css.css b/demos/mini_leaderboard/assets/custom_css.css new file mode 100644 index 0000000000000000000000000000000000000000..91a5ff7d986e4b2026bed2175bdf99f847ed05a0 --- /dev/null +++ b/demos/mini_leaderboard/assets/custom_css.css @@ -0,0 +1,87 @@ +/* Hides the final AutoEvalColumn */ +#llm-benchmark-tab-table table td:last-child, +#llm-benchmark-tab-table table th:last-child { + display: none; +} + +/* Limit the width of the first AutoEvalColumn so that names don't expand too much */ +table td:first-child, +table th:first-child { + max-width: 400px; + overflow: auto; + white-space: nowrap; +} + +/* Full width space */ +.gradio-container { + max-width: 95%!important; +} + +/* Text style and margins */ +.markdown-text { + font-size: 16px !important; +} + +#models-to-add-text { + font-size: 18px !important; +} + +#citation-button span { + font-size: 16px !important; +} + +#citation-button textarea { + font-size: 16px !important; +} + +#citation-button > label > button { + margin: 6px; + transform: scale(1.3); +} + +#search-bar-table-box > div:first-child { + background: none; + border: none; +} + +#search-bar { + padding: 0px; +} + +.tab-buttons button { + font-size: 20px; +} + +/* Filters style */ +#filter_type{ + border: 0; + padding-left: 0; + padding-top: 0; +} +#filter_type label { + display: flex; +} +#filter_type label > span{ + margin-top: var(--spacing-lg); + margin-right: 0.5em; +} +#filter_type label > .wrap{ + width: 103px; +} +#filter_type label > .wrap .wrap-inner{ + padding: 2px; +} +#filter_type label > .wrap .wrap-inner input{ + width: 1px +} +#filter-columns-type{ + border:0; + padding:0.5; +} +#filter-columns-size{ + border:0; + padding:0.5; +} +#box-filter > .form{ + border: 0 +} \ No newline at end of file diff --git a/demos/mini_leaderboard/assets/leaderboard_data.json b/demos/mini_leaderboard/assets/leaderboard_data.json new file mode 100644 index 0000000000000000000000000000000000000000..e0d3af4b3db66a038e84d5a47f8b52b994f0387a --- /dev/null +++ b/demos/mini_leaderboard/assets/leaderboard_data.json @@ -0,0 +1 @@ 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\ No newline at end of file diff --git a/demos/mini_leaderboard/run.ipynb b/demos/mini_leaderboard/run.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..26a403326ad7fd8f248732781d00364f1ea939a7 --- /dev/null +++ b/demos/mini_leaderboard/run.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: mini_leaderboard"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "os.mkdir('assets')\n", "!wget -q -O assets/__init__.py https://github.com/gradio-app/gradio/raw/main/demo/mini_leaderboard/assets/__init__.py\n", "!wget -q -O assets/custom_css.css https://github.com/gradio-app/gradio/raw/main/demo/mini_leaderboard/assets/custom_css.css\n", "!wget -q -O assets/leaderboard_data.json https://github.com/gradio-app/gradio/raw/main/demo/mini_leaderboard/assets/leaderboard_data.json"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import pandas as pd\n", "from pathlib import Path\n", "\n", "abs_path = Path(__file__).parent.absolute()\n", "\n", "df = pd.read_json(str(abs_path / \"assets/leaderboard_data.json\"))\n", "invisible_df = df.copy()\n", "\n", "\n", "COLS = [\n", " \"T\",\n", " \"Model\",\n", " \"Average \u2b06\ufe0f\",\n", " \"ARC\",\n", " \"HellaSwag\",\n", " \"MMLU\",\n", " \"TruthfulQA\",\n", " \"Winogrande\",\n", " \"GSM8K\",\n", " \"Type\",\n", " \"Architecture\",\n", " \"Precision\",\n", " \"Merged\",\n", " \"Hub License\",\n", " \"#Params (B)\",\n", " \"Hub \u2764\ufe0f\",\n", " \"Model sha\",\n", " \"model_name_for_query\",\n", "]\n", "ON_LOAD_COLS = [\n", " \"T\",\n", " \"Model\",\n", " \"Average \u2b06\ufe0f\",\n", " \"ARC\",\n", " \"HellaSwag\",\n", " \"MMLU\",\n", " \"TruthfulQA\",\n", " \"Winogrande\",\n", " \"GSM8K\",\n", " \"model_name_for_query\",\n", "]\n", "TYPES = [\n", " \"str\",\n", " \"markdown\",\n", " \"number\",\n", " \"number\",\n", " \"number\",\n", " \"number\",\n", " \"number\",\n", " \"number\",\n", " \"number\",\n", " \"str\",\n", " \"str\",\n", " \"str\",\n", " \"str\",\n", " \"bool\",\n", " \"str\",\n", " \"number\",\n", " \"number\",\n", " \"bool\",\n", " \"str\",\n", " \"bool\",\n", " \"bool\",\n", " \"str\",\n", "]\n", "NUMERIC_INTERVALS = {\n", " \"?\": pd.Interval(-1, 0, closed=\"right\"),\n", " \"~1.5\": pd.Interval(0, 2, closed=\"right\"),\n", " \"~3\": pd.Interval(2, 4, closed=\"right\"),\n", " \"~7\": pd.Interval(4, 9, closed=\"right\"),\n", " \"~13\": pd.Interval(9, 20, closed=\"right\"),\n", " \"~35\": pd.Interval(20, 45, closed=\"right\"),\n", " \"~60\": pd.Interval(45, 70, closed=\"right\"),\n", " \"70+\": pd.Interval(70, 10000, closed=\"right\"),\n", "}\n", "MODEL_TYPE = [str(s) for s in df[\"T\"].unique()]\n", "Precision = [str(s) for s in df[\"Precision\"].unique()]\n", "\n", "\n", "# Searching and filtering\n", "def update_table(\n", " hidden_df: pd.DataFrame,\n", " columns: list,\n", " type_query: list,\n", " precision_query: str,\n", " size_query: list,\n", " query: str,\n", "):\n", " filtered_df = filter_models(hidden_df, type_query, size_query, precision_query)\n", " filtered_df = filter_queries(query, filtered_df)\n", " df = select_columns(filtered_df, columns)\n", " return df\n", "\n", "\n", "def search_table(df: pd.DataFrame, query: str) -> pd.DataFrame:\n", " return df[(df[\"model_name_for_query\"].str.contains(query, case=False))]\n", "\n", "\n", "def select_columns(df: pd.DataFrame, columns: list) -> pd.DataFrame:\n", " # We use COLS to maintain sorting\n", " filtered_df = df[[c for c in COLS if c in df.columns and c in columns]]\n", " return filtered_df\n", "\n", "\n", "def filter_queries(query: str, filtered_df: pd.DataFrame) -> pd.DataFrame:\n", " final_df = []\n", " if query != \"\":\n", " queries = [q.strip() for q in query.split(\";\")]\n", " for _q in queries:\n", " _q = _q.strip()\n", " if _q != \"\":\n", " temp_filtered_df = search_table(filtered_df, _q)\n", " if len(temp_filtered_df) > 0:\n", " final_df.append(temp_filtered_df)\n", " if len(final_df) > 0:\n", " filtered_df = pd.concat(final_df)\n", " filtered_df = filtered_df.drop_duplicates(\n", " subset=[\"Model\", \"Precision\", \"Model sha\"]\n", " )\n", "\n", " return filtered_df\n", "\n", "\n", "def filter_models(\n", " df: pd.DataFrame,\n", " type_query: list,\n", " size_query: list,\n", " precision_query: list,\n", ") -> pd.DataFrame:\n", " # Show all models\n", " filtered_df = df\n", "\n", " type_emoji = [t[0] for t in type_query]\n", " filtered_df = filtered_df.loc[df[\"T\"].isin(type_emoji)]\n", " filtered_df = filtered_df.loc[df[\"Precision\"].isin(precision_query + [\"None\"])]\n", "\n", " numeric_interval = pd.IntervalIndex(\n", " sorted([NUMERIC_INTERVALS[s] for s in size_query])\n", " )\n", " params_column = pd.to_numeric(df[\"#Params (B)\"], errors=\"coerce\")\n", " mask = params_column.apply(lambda x: any(numeric_interval.contains(x)))\n", " filtered_df = filtered_df.loc[mask]\n", "\n", " return filtered_df\n", "\n", "\n", "demo = gr.Blocks(css=str(abs_path / \"assets/leaderboard_data.json\"))\n", "with demo:\n", " gr.Markdown(\"\"\"Test Space of the LLM Leaderboard\"\"\", elem_classes=\"markdown-text\")\n", "\n", " with gr.Tabs(elem_classes=\"tab-buttons\") as tabs:\n", " with gr.TabItem(\"\ud83c\udfc5 LLM Benchmark\", elem_id=\"llm-benchmark-tab-table\", id=0):\n", " with gr.Row():\n", " with gr.Column():\n", " with gr.Row():\n", " search_bar = gr.Textbox(\n", " placeholder=\" \ud83d\udd0d Search for your model (separate multiple queries with `;`) and press ENTER...\",\n", " show_label=False,\n", " elem_id=\"search-bar\",\n", " )\n", " with gr.Row():\n", " shown_columns = gr.CheckboxGroup(\n", " choices=COLS,\n", " value=ON_LOAD_COLS,\n", " label=\"Select columns to show\",\n", " elem_id=\"column-select\",\n", " interactive=True,\n", " )\n", " with gr.Column(min_width=320):\n", " filter_columns_type = gr.CheckboxGroup(\n", " label=\"Model types\",\n", " choices=MODEL_TYPE,\n", " value=MODEL_TYPE,\n", " interactive=True,\n", " elem_id=\"filter-columns-type\",\n", " )\n", " filter_columns_precision = gr.CheckboxGroup(\n", " label=\"Precision\",\n", " choices=Precision,\n", " value=Precision,\n", " interactive=True,\n", " elem_id=\"filter-columns-precision\",\n", " )\n", " filter_columns_size = gr.CheckboxGroup(\n", " label=\"Model sizes (in billions of parameters)\",\n", " choices=list(NUMERIC_INTERVALS.keys()),\n", " value=list(NUMERIC_INTERVALS.keys()),\n", " interactive=True,\n", " elem_id=\"filter-columns-size\",\n", " )\n", "\n", " leaderboard_table = gr.components.Dataframe(\n", " value=df[ON_LOAD_COLS],\n", " headers=ON_LOAD_COLS,\n", " datatype=TYPES,\n", " elem_id=\"leaderboard-table\",\n", " interactive=False,\n", " visible=True,\n", " column_widths=[\"2%\", \"33%\"],\n", " )\n", "\n", " # Dummy leaderboard for handling the case when the user uses backspace key\n", " hidden_leaderboard_table_for_search = gr.components.Dataframe(\n", " value=invisible_df[COLS],\n", " headers=COLS,\n", " datatype=TYPES,\n", " visible=False,\n", " )\n", " search_bar.submit(\n", " update_table,\n", " [\n", " hidden_leaderboard_table_for_search,\n", " shown_columns,\n", " filter_columns_type,\n", " filter_columns_precision,\n", " filter_columns_size,\n", " search_bar,\n", " ],\n", " leaderboard_table,\n", " )\n", " for selector in [\n", " shown_columns,\n", " filter_columns_type,\n", " filter_columns_precision,\n", " filter_columns_size,\n", " ]:\n", " selector.change(\n", " update_table,\n", " [\n", " hidden_leaderboard_table_for_search,\n", " shown_columns,\n", " filter_columns_type,\n", " filter_columns_precision,\n", " filter_columns_size,\n", " search_bar,\n", " ],\n", " leaderboard_table,\n", " queue=True,\n", " )\n", "\n", "\n", "if __name__ == \"__main__\":\n", " demo.queue(default_concurrency_limit=40).launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} \ No newline at end of file diff --git a/demos/mini_leaderboard/run.py b/demos/mini_leaderboard/run.py new file mode 100644 index 0000000000000000000000000000000000000000..3204e58c730cdbc5b7738df232ed9f09f0a8e8d6 --- /dev/null +++ b/demos/mini_leaderboard/run.py @@ -0,0 +1,244 @@ +import gradio as gr +import pandas as pd +from pathlib import Path + +abs_path = Path(__file__).parent.absolute() + +df = pd.read_json(str(abs_path / "assets/leaderboard_data.json")) +invisible_df = df.copy() + + +COLS = [ + "T", + "Model", + "Average ⬆️", + "ARC", + "HellaSwag", + "MMLU", + "TruthfulQA", + "Winogrande", + "GSM8K", + "Type", + "Architecture", + "Precision", + "Merged", + "Hub License", + "#Params (B)", + "Hub ❤️", + "Model sha", + "model_name_for_query", +] +ON_LOAD_COLS = [ + "T", + "Model", + "Average ⬆️", + "ARC", + "HellaSwag", + "MMLU", + "TruthfulQA", + "Winogrande", + "GSM8K", + "model_name_for_query", +] +TYPES = [ + "str", + "markdown", + "number", + "number", + "number", + "number", + "number", + "number", + "number", + "str", + "str", + "str", + "str", + "bool", + "str", + "number", + "number", + "bool", + "str", + "bool", + "bool", + "str", +] +NUMERIC_INTERVALS = { + "?": pd.Interval(-1, 0, closed="right"), + "~1.5": pd.Interval(0, 2, closed="right"), + "~3": pd.Interval(2, 4, closed="right"), + "~7": pd.Interval(4, 9, closed="right"), + "~13": pd.Interval(9, 20, closed="right"), + "~35": pd.Interval(20, 45, closed="right"), + "~60": pd.Interval(45, 70, closed="right"), + "70+": pd.Interval(70, 10000, closed="right"), +} +MODEL_TYPE = [str(s) for s in df["T"].unique()] +Precision = [str(s) for s in df["Precision"].unique()] + + +# Searching and filtering +def update_table( + hidden_df: pd.DataFrame, + columns: list, + type_query: list, + precision_query: str, + size_query: list, + query: str, +): + filtered_df = filter_models(hidden_df, type_query, size_query, precision_query) + filtered_df = filter_queries(query, filtered_df) + df = select_columns(filtered_df, columns) + return df + + +def search_table(df: pd.DataFrame, query: str) -> pd.DataFrame: + return df[(df["model_name_for_query"].str.contains(query, case=False))] + + +def select_columns(df: pd.DataFrame, columns: list) -> pd.DataFrame: + # We use COLS to maintain sorting + filtered_df = df[[c for c in COLS if c in df.columns and c in columns]] + return filtered_df + + +def filter_queries(query: str, filtered_df: pd.DataFrame) -> pd.DataFrame: + final_df = [] + if query != "": + queries = [q.strip() for q in query.split(";")] + for _q in queries: + _q = _q.strip() + if _q != "": + temp_filtered_df = search_table(filtered_df, _q) + if len(temp_filtered_df) > 0: + final_df.append(temp_filtered_df) + if len(final_df) > 0: + filtered_df = pd.concat(final_df) + filtered_df = filtered_df.drop_duplicates( + subset=["Model", "Precision", "Model sha"] + ) + + return filtered_df + + +def filter_models( + df: pd.DataFrame, + type_query: list, + size_query: list, + precision_query: list, +) -> pd.DataFrame: + # Show all models + filtered_df = df + + type_emoji = [t[0] for t in type_query] + filtered_df = filtered_df.loc[df["T"].isin(type_emoji)] + filtered_df = filtered_df.loc[df["Precision"].isin(precision_query + ["None"])] + + numeric_interval = pd.IntervalIndex( + sorted([NUMERIC_INTERVALS[s] for s in size_query]) + ) + params_column = pd.to_numeric(df["#Params (B)"], errors="coerce") + mask = params_column.apply(lambda x: any(numeric_interval.contains(x))) + filtered_df = filtered_df.loc[mask] + + return filtered_df + + +demo = gr.Blocks(css=str(abs_path / "assets/leaderboard_data.json")) +with demo: + gr.Markdown("""Test Space of the LLM Leaderboard""", elem_classes="markdown-text") + + with gr.Tabs(elem_classes="tab-buttons") as tabs: + with gr.TabItem("🏅 LLM Benchmark", elem_id="llm-benchmark-tab-table", id=0): + with gr.Row(): + with gr.Column(): + with gr.Row(): + search_bar = gr.Textbox( + placeholder=" 🔍 Search for your model (separate multiple queries with `;`) and press ENTER...", + show_label=False, + elem_id="search-bar", + ) + with gr.Row(): + shown_columns = gr.CheckboxGroup( + choices=COLS, + value=ON_LOAD_COLS, + label="Select columns to show", + elem_id="column-select", + interactive=True, + ) + with gr.Column(min_width=320): + filter_columns_type = gr.CheckboxGroup( + label="Model types", + choices=MODEL_TYPE, + value=MODEL_TYPE, + interactive=True, + elem_id="filter-columns-type", + ) + filter_columns_precision = gr.CheckboxGroup( + label="Precision", + choices=Precision, + value=Precision, + interactive=True, + elem_id="filter-columns-precision", + ) + filter_columns_size = gr.CheckboxGroup( + label="Model sizes (in billions of parameters)", + choices=list(NUMERIC_INTERVALS.keys()), + value=list(NUMERIC_INTERVALS.keys()), + interactive=True, + elem_id="filter-columns-size", + ) + + leaderboard_table = gr.components.Dataframe( + value=df[ON_LOAD_COLS], + headers=ON_LOAD_COLS, + datatype=TYPES, + elem_id="leaderboard-table", + interactive=False, + visible=True, + column_widths=["2%", "33%"], + ) + + # Dummy leaderboard for handling the case when the user uses backspace key + hidden_leaderboard_table_for_search = gr.components.Dataframe( + value=invisible_df[COLS], + headers=COLS, + datatype=TYPES, + visible=False, + ) + search_bar.submit( + update_table, + [ + hidden_leaderboard_table_for_search, + shown_columns, + filter_columns_type, + filter_columns_precision, + filter_columns_size, + search_bar, + ], + leaderboard_table, + ) + for selector in [ + shown_columns, + filter_columns_type, + filter_columns_precision, + filter_columns_size, + ]: + selector.change( + update_table, + [ + hidden_leaderboard_table_for_search, + shown_columns, + filter_columns_type, + filter_columns_precision, + filter_columns_size, + search_bar, + ], + leaderboard_table, + queue=True, + ) + + +if __name__ == "__main__": + demo.queue(default_concurrency_limit=40).launch() diff --git a/demos/model3D/files/Bunny.obj b/demos/model3D/files/Bunny.obj new file mode 100644 index 0000000000000000000000000000000000000000..9baeb363cce8feb5dd62ecaf8d64a14b6c50ce37 --- /dev/null +++ b/demos/model3D/files/Bunny.obj @@ -0,0 +1,7474 @@ +# OBJ file format with ext .obj +# vertex count = 2503 +# face count = 4968 +v -3.4101800e-003 1.3031957e-001 2.1754370e-002 +v -8.1719160e-002 1.5250145e-001 2.9656090e-002 +v -3.0543480e-002 1.2477885e-001 1.0983400e-003 +v -2.4901590e-002 1.1211138e-001 3.7560240e-002 +v -1.8405680e-002 1.7843055e-001 -2.4219580e-002 +v 1.9067940e-002 1.2144925e-001 3.1968440e-002 +v 6.0412000e-003 1.2494359e-001 3.2652890e-002 +v -1.3469030e-002 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", 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792 603 601 +f 793 601 843 +f 844 669 794 +f 599 843 601 +f 598 844 843 +f 597 845 844 +f 845 675 669 +f 845 596 591 +f 780 783 778 +# 1610 faces, 0 coords texture + +# End of File diff --git a/demos/model3D/files/sofia.stl b/demos/model3D/files/sofia.stl new file mode 100644 index 0000000000000000000000000000000000000000..8a811c851675350bc5f9ab0d1f0eff69651104ae Binary files /dev/null and b/demos/model3D/files/sofia.stl differ diff --git a/demos/model3D/files/source.txt b/demos/model3D/files/source.txt new file mode 100644 index 0000000000000000000000000000000000000000..95f4bcc925f0bf5cf6a00913e13532fd0616f77a --- /dev/null +++ b/demos/model3D/files/source.txt @@ -0,0 +1,13 @@ +Stanford Bunny: +https://graphics.stanford.edu/data/3Dscanrep/ +https://graphics.stanford.edu/~mdfisher/Data/Meshes/bunny.obj + +Duck & Fox: +https://github.com/KhronosGroup/glTF-Sample-Models + +Face: +https://github.com/mikedh/trimesh/tree/main/models + +NASA SOFIA: +https://nasa3d.arc.nasa.gov/detail/sofia +https://github.com/nasa/NASA-3D-Resources/blob/master/3D%20Models/SOFIA/Fuselage_top.stl \ No newline at end of file diff --git a/demos/model3D/run.ipynb b/demos/model3D/run.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..93d8e7e11482282374310ac61760312b6d1699cc --- /dev/null +++ b/demos/model3D/run.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: model3D"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "os.mkdir('files')\n", "!wget -q -O files/Bunny.obj https://github.com/gradio-app/gradio/raw/main/demo/model3D/files/Bunny.obj\n", "!wget -q -O files/Duck.glb https://github.com/gradio-app/gradio/raw/main/demo/model3D/files/Duck.glb\n", "!wget -q -O files/Fox.gltf https://github.com/gradio-app/gradio/raw/main/demo/model3D/files/Fox.gltf\n", "!wget -q -O files/face.obj https://github.com/gradio-app/gradio/raw/main/demo/model3D/files/face.obj\n", "!wget -q -O files/sofia.stl https://github.com/gradio-app/gradio/raw/main/demo/model3D/files/sofia.stl\n", "!wget -q -O files/source.txt https://github.com/gradio-app/gradio/raw/main/demo/model3D/files/source.txt"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import os\n", "\n", "\n", "def load_mesh(mesh_file_name):\n", " return mesh_file_name\n", "\n", "\n", "demo = gr.Interface(\n", " fn=load_mesh,\n", " inputs=gr.Model3D(),\n", " outputs=gr.Model3D(\n", " clear_color=[0.0, 0.0, 0.0, 0.0], label=\"3D Model\"),\n", " examples=[\n", " [os.path.join(os.path.abspath(''), \"files/Bunny.obj\")],\n", " [os.path.join(os.path.abspath(''), \"files/Duck.glb\")],\n", " [os.path.join(os.path.abspath(''), \"files/Fox.gltf\")],\n", " [os.path.join(os.path.abspath(''), \"files/face.obj\")],\n", " [os.path.join(os.path.abspath(''), \"files/sofia.stl\")],\n", " [\"https://huggingface.co/datasets/dylanebert/3dgs/resolve/main/bonsai/bonsai-7k-mini.splat\"],\n", " [\"https://huggingface.co/datasets/dylanebert/3dgs/resolve/main/luigi/luigi.ply\"],\n", " ],\n", " cache_examples=True\n", ")\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} \ No newline at end of file diff --git a/demos/model3D/run.py b/demos/model3D/run.py new file mode 100644 index 0000000000000000000000000000000000000000..acd3f14652b38b9abefd7bbe11ac5e1853470ab3 --- /dev/null +++ b/demos/model3D/run.py @@ -0,0 +1,27 @@ +import gradio as gr +import os + + +def load_mesh(mesh_file_name): + return mesh_file_name + + +demo = gr.Interface( + fn=load_mesh, + inputs=gr.Model3D(), + outputs=gr.Model3D( + clear_color=[0.0, 0.0, 0.0, 0.0], label="3D Model"), + examples=[ + [os.path.join(os.path.dirname(__file__), "files/Bunny.obj")], + [os.path.join(os.path.dirname(__file__), "files/Duck.glb")], + [os.path.join(os.path.dirname(__file__), "files/Fox.gltf")], + [os.path.join(os.path.dirname(__file__), "files/face.obj")], + [os.path.join(os.path.dirname(__file__), "files/sofia.stl")], + ["https://huggingface.co/datasets/dylanebert/3dgs/resolve/main/bonsai/bonsai-7k-mini.splat"], + ["https://huggingface.co/datasets/dylanebert/3dgs/resolve/main/luigi/luigi.ply"], + ], + cache_examples=True +) + +if __name__ == "__main__": + demo.launch() diff --git a/demos/native_plots/bar_plot_demo.py b/demos/native_plots/bar_plot_demo.py new file mode 100644 index 0000000000000000000000000000000000000000..a4432e121bcbc844df6b4a5590d51e958be3be7e --- /dev/null +++ b/demos/native_plots/bar_plot_demo.py @@ -0,0 +1,111 @@ +import gradio as gr +import pandas as pd + +from vega_datasets import data + +barley = data.barley() +simple = pd.DataFrame({ + 'a': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I'], + 'b': [28, 55, 43, 91, 81, 53, 19, 87, 52] +}) + +def bar_plot_fn(display): + if display == "simple": + return gr.BarPlot( + simple, + x="a", + y="b", + color=None, + group=None, + title="Simple Bar Plot with made up data", + tooltip=['a', 'b'], + y_lim=[20, 100], + x_title=None, + y_title=None, + vertical=True, + ) + elif display == "stacked": + return gr.BarPlot( + barley, + x="variety", + y="yield", + color="site", + group=None, + title="Barley Yield Data", + tooltip=['variety', 'site'], + y_lim=None, + x_title=None, + y_title=None, + vertical=True, + ) + elif display == "grouped": + return gr.BarPlot( + barley.astype({"year": str}), + x="year", + y="yield", + color="year", + group="site", + title="Barley Yield by Year and Site", + tooltip=["yield", "site", "year"], + y_lim=None, + x_title=None, + y_title=None, + vertical=True, + ) + elif display == "simple-horizontal": + return gr.BarPlot( + simple, + x="a", + y="b", + color=None, + group=None, + title="Simple Bar Plot with made up data", + tooltip=['a', 'b'], + y_lim=[20, 100], + x_title="Variable A", + y_title="Variable B", + vertical=False, + ) + elif display == "stacked-horizontal": + return gr.BarPlot( + barley, + x="variety", + y="yield", + color="site", + group=None, + title="Barley Yield Data", + tooltip=['variety', 'site'], + y_lim=None, + x_title=None, + y_title=None, + vertical=False, + ) + elif display == "grouped-horizontal": + return gr.BarPlot( + barley.astype({"year": str}), + x="year", + y="yield", + color="year", + group="site", + title="Barley Yield by Year and Site", + group_title="", + tooltip=["yield", "site", "year"], + y_lim=None, + x_title=None, + y_title=None, + vertical=False + ) + + +with gr.Blocks() as bar_plot: + with gr.Row(): + with gr.Column(): + display = gr.Dropdown( + choices=["simple", "stacked", "grouped", "simple-horizontal", "stacked-horizontal", "grouped-horizontal"], + value="simple", + label="Type of Bar Plot" + ) + with gr.Column(): + plot = gr.BarPlot(show_label=False, show_actions_button=True) + display.change(bar_plot_fn, inputs=display, outputs=plot) + bar_plot.load(fn=bar_plot_fn, inputs=display, outputs=plot) diff --git a/demos/native_plots/line_plot_demo.py b/demos/native_plots/line_plot_demo.py new file mode 100644 index 0000000000000000000000000000000000000000..49b87d8db2f4a3303f616ccb29ff34a722c770b1 --- /dev/null +++ b/demos/native_plots/line_plot_demo.py @@ -0,0 +1,94 @@ +import gradio as gr +from vega_datasets import data + +stocks = data.stocks() +gapminder = data.gapminder() +gapminder = gapminder.loc[ + gapminder.country.isin(["Argentina", "Australia", "Afghanistan"]) +] +climate = data.climate() +seattle_weather = data.seattle_weather() + + +def line_plot_fn(dataset): + if dataset == "stocks": + return gr.LinePlot( + stocks, + x="date", + y="price", + color="symbol", + x_lim=None, + y_lim=None, + stroke_dash=None, + tooltip=['date', 'price', 'symbol'], + overlay_point=False, + title="Stock Prices", + stroke_dash_legend_title=None, + height=300, + width=500 + ) + elif dataset == "climate": + return gr.LinePlot( + climate, + x="DATE", + y="HLY-TEMP-NORMAL", + color=None, + x_lim=None, + y_lim=[250, 500], + stroke_dash=None, + tooltip=['DATE', 'HLY-TEMP-NORMAL'], + overlay_point=False, + title="Climate", + stroke_dash_legend_title=None, + height=300, + width=500 + ) + elif dataset == "seattle_weather": + return gr.LinePlot( + seattle_weather, + x="date", + y="temp_min", + color=None, + x_lim=None, + y_lim=None, + stroke_dash=None, + tooltip=["weather", "date"], + overlay_point=True, + title="Seattle Weather", + stroke_dash_legend_title=None, + height=300, + width=500 + ) + elif dataset == "gapminder": + return gr.LinePlot( + gapminder, + x="year", + y="life_expect", + color="country", + x_lim=[1950, 2010], + y_lim=None, + stroke_dash="cluster", + tooltip=['country', 'life_expect'], + overlay_point=False, + title="Life expectancy for countries", + stroke_dash_legend_title="Country Cluster", + height=300, + width=500 + ) + + +with gr.Blocks() as line_plot: + with gr.Row(): + with gr.Column(): + dataset = gr.Dropdown( + choices=["stocks", "climate", "seattle_weather", "gapminder"], + value="stocks", + ) + with gr.Column(): + plot = gr.LinePlot() + dataset.change(line_plot_fn, inputs=dataset, outputs=plot) + line_plot.load(fn=line_plot_fn, inputs=dataset, outputs=plot) + + +if __name__ == "__main__": + line_plot.launch() diff --git a/demos/native_plots/requirements.txt b/demos/native_plots/requirements.txt new file mode 100644 index 0000000000000000000000000000000000000000..d1c8a7ae0396d12417907feb8ef43fb4bcc8e89c --- /dev/null +++ b/demos/native_plots/requirements.txt @@ -0,0 +1 @@ +vega_datasets \ No newline at end of file diff --git a/demos/native_plots/run.ipynb b/demos/native_plots/run.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..f79c3ad9856bd51e1174f555d319ac8c68fccf57 --- /dev/null +++ b/demos/native_plots/run.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: native_plots"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio vega_datasets"]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/native_plots/bar_plot_demo.py\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/native_plots/line_plot_demo.py\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/native_plots/scatter_plot_demo.py"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "\n", "from scatter_plot_demo import scatter_plot\n", "from line_plot_demo import line_plot\n", "from bar_plot_demo import bar_plot\n", "\n", "\n", "with gr.Blocks() as demo:\n", " with gr.Tabs():\n", " with gr.TabItem(\"Scatter Plot\"):\n", " scatter_plot.render()\n", " with gr.TabItem(\"Line Plot\"):\n", " line_plot.render()\n", " with gr.TabItem(\"Bar Plot\"):\n", " bar_plot.render()\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} \ No newline at end of file diff --git a/demos/native_plots/run.py b/demos/native_plots/run.py new file mode 100644 index 0000000000000000000000000000000000000000..3ed9ed8309fdb01401ef7c234884ea36ba9dd004 --- /dev/null +++ b/demos/native_plots/run.py @@ -0,0 +1,18 @@ +import gradio as gr + +from scatter_plot_demo import scatter_plot +from line_plot_demo import line_plot +from bar_plot_demo import bar_plot + + +with gr.Blocks() as demo: + with gr.Tabs(): + with gr.TabItem("Scatter Plot"): + scatter_plot.render() + with gr.TabItem("Line Plot"): + line_plot.render() + with gr.TabItem("Bar Plot"): + bar_plot.render() + +if __name__ == "__main__": + demo.launch() diff --git a/demos/native_plots/scatter_plot_demo.py b/demos/native_plots/scatter_plot_demo.py new file mode 100644 index 0000000000000000000000000000000000000000..3ae129ea9d3a71717ce6bcd34b94069e3cece2a7 --- /dev/null +++ b/demos/native_plots/scatter_plot_demo.py @@ -0,0 +1,47 @@ +import gradio as gr + +from vega_datasets import data + +cars = data.cars() +iris = data.iris() + + +def scatter_plot_fn(dataset): + if dataset == "iris": + return gr.ScatterPlot( + value=iris, + x="petalWidth", + y="petalLength", + color="species", + title="Iris Dataset", + color_legend_title="Species", + x_title="Petal Width", + y_title="Petal Length", + tooltip=["petalWidth", "petalLength", "species"], + caption="", + ) + else: + return gr.ScatterPlot( + value=cars, + x="Horsepower", + y="Miles_per_Gallon", + color="Origin", + tooltip="Name", + title="Car Data", + y_title="Miles per Gallon", + color_legend_title="Origin of Car", + caption="MPG vs Horsepower of various cars", + ) + + +with gr.Blocks() as scatter_plot: + with gr.Row(): + with gr.Column(): + dataset = gr.Dropdown(choices=["cars", "iris"], value="cars") + with gr.Column(): + plot = gr.ScatterPlot(show_label=False) + dataset.change(scatter_plot_fn, inputs=dataset, outputs=plot) + scatter_plot.load(fn=scatter_plot_fn, inputs=dataset, outputs=plot) + +if __name__ == "__main__": + scatter_plot.launch() diff --git a/demos/reverse_audio/audio/cantina.wav b/demos/reverse_audio/audio/cantina.wav new file mode 100644 index 0000000000000000000000000000000000000000..41f020438468229763ec4a2321325e5916e09106 Binary files /dev/null and b/demos/reverse_audio/audio/cantina.wav differ diff --git a/demos/reverse_audio/audio/recording1.wav b/demos/reverse_audio/audio/recording1.wav new file mode 100644 index 0000000000000000000000000000000000000000..a58ba5006d4afbfce2b13764e0fc8768286a340d Binary files /dev/null and b/demos/reverse_audio/audio/recording1.wav differ diff --git a/demos/reverse_audio/run.ipynb b/demos/reverse_audio/run.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..fb38bf537cdcef5a13c5229b5136064759f0c023 --- /dev/null +++ b/demos/reverse_audio/run.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: reverse_audio"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "os.mkdir('audio')\n", "!wget -q -O audio/cantina.wav https://github.com/gradio-app/gradio/raw/main/demo/reverse_audio/audio/cantina.wav\n", "!wget -q -O audio/recording1.wav https://github.com/gradio-app/gradio/raw/main/demo/reverse_audio/audio/recording1.wav"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import os\n", "\n", "import numpy as np\n", "\n", "import gradio as gr\n", "\n", "\n", "def reverse_audio(audio):\n", " sr, data = audio\n", " return (sr, np.flipud(data))\n", "\n", "\n", "input_audio = gr.Audio(\n", " sources=[\"microphone\"],\n", " waveform_options=gr.WaveformOptions(\n", " waveform_color=\"#01C6FF\",\n", " waveform_progress_color=\"#0066B4\",\n", " skip_length=2,\n", " show_controls=False,\n", " ),\n", ")\n", "demo = gr.Interface(\n", " fn=reverse_audio,\n", " inputs=input_audio,\n", " outputs=\"audio\"\n", ")\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} \ No newline at end of file diff --git a/demos/reverse_audio/run.py b/demos/reverse_audio/run.py new file mode 100644 index 0000000000000000000000000000000000000000..ac3227aeec62c4fce04875a576de31f11ee6a3fe --- /dev/null +++ b/demos/reverse_audio/run.py @@ -0,0 +1,29 @@ +import os + +import numpy as np + +import gradio as gr + + +def reverse_audio(audio): + sr, data = audio + return (sr, np.flipud(data)) + + +input_audio = gr.Audio( + sources=["microphone"], + waveform_options=gr.WaveformOptions( + waveform_color="#01C6FF", + waveform_progress_color="#0066B4", + skip_length=2, + show_controls=False, + ), +) +demo = gr.Interface( + fn=reverse_audio, + inputs=input_audio, + outputs="audio" +) + +if __name__ == "__main__": + demo.launch() diff --git a/demos/reverse_audio/screenshot.png b/demos/reverse_audio/screenshot.png new file mode 100644 index 0000000000000000000000000000000000000000..796151630ac2bb931d09cfa511c0084a6fc391a1 Binary files /dev/null and b/demos/reverse_audio/screenshot.png differ diff --git a/demos/stream_audio/run.ipynb b/demos/stream_audio/run.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..980bdde941e7dffade21978f45600ed42382f8cb --- /dev/null +++ b/demos/stream_audio/run.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: stream_audio"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import numpy as np\n", "import time\n", "\n", "def add_to_stream(audio, instream):\n", " time.sleep(1)\n", " if audio is None:\n", " return gr.Audio(), instream\n", " if instream is None:\n", " ret = audio\n", " else:\n", " ret = (audio[0], np.concatenate((instream[1], audio[1])))\n", " return ret, ret\n", "\n", "\n", "with gr.Blocks() as demo:\n", " inp = gr.Audio(sources=[\"microphone\"])\n", " out = gr.Audio()\n", " stream = gr.State()\n", " clear = gr.Button(\"Clear\")\n", "\n", " inp.stream(add_to_stream, [inp, stream], [out, stream])\n", " clear.click(lambda: [None, None, None], None, [inp, out, stream])\n", "\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} \ No newline at end of file diff --git a/demos/stream_audio/run.py b/demos/stream_audio/run.py new file mode 100644 index 0000000000000000000000000000000000000000..8b0af573d4500f0dc29dd1539781cb4ff0b49889 --- /dev/null +++ b/demos/stream_audio/run.py @@ -0,0 +1,27 @@ +import gradio as gr +import numpy as np +import time + +def add_to_stream(audio, instream): + time.sleep(1) + if audio is None: + return gr.Audio(), instream + if instream is None: + ret = audio + else: + ret = (audio[0], np.concatenate((instream[1], audio[1]))) + return ret, ret + + +with gr.Blocks() as demo: + inp = gr.Audio(sources=["microphone"]) + out = gr.Audio() + stream = gr.State() + clear = gr.Button("Clear") + + inp.stream(add_to_stream, [inp, stream], [out, stream]) + clear.click(lambda: [None, None, None], None, [inp, out, stream]) + + +if __name__ == "__main__": + demo.launch() \ No newline at end of file diff --git a/demos/stream_frames/run.ipynb b/demos/stream_frames/run.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..9543887421138fcdd81040fe581d38e582c1edee --- /dev/null +++ b/demos/stream_frames/run.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: stream_frames"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import numpy as np\n", "\n", "def flip(im):\n", " return np.flipud(im)\n", "\n", "demo = gr.Interface(\n", " flip, \n", " gr.Image(sources=[\"webcam\"], streaming=True), \n", " \"image\",\n", " live=True\n", ")\n", "if __name__ == \"__main__\":\n", " demo.launch()\n", " "]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} \ No newline at end of file diff --git a/demos/stream_frames/run.py b/demos/stream_frames/run.py new file mode 100644 index 0000000000000000000000000000000000000000..547fc11eec2f626fd4aa0baa13189abdd951d5cc --- /dev/null +++ b/demos/stream_frames/run.py @@ -0,0 +1,15 @@ +import gradio as gr +import numpy as np + +def flip(im): + return np.flipud(im) + +demo = gr.Interface( + flip, + gr.Image(sources=["webcam"], streaming=True), + "image", + live=True +) +if __name__ == "__main__": + demo.launch() + \ No newline at end of file diff --git a/demos/stt_or_tts/run.ipynb b/demos/stt_or_tts/run.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..f1608fcaf52e70947e91c19182896debceb85979 --- /dev/null +++ b/demos/stt_or_tts/run.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: stt_or_tts"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "\n", "tts_examples = [\n", " \"I love learning machine learning\",\n", " \"How do you do?\",\n", "]\n", "\n", "tts_demo = gr.load(\n", " \"huggingface/facebook/fastspeech2-en-ljspeech\",\n", " title=None,\n", " examples=tts_examples,\n", " description=\"Give me something to say!\",\n", ")\n", "\n", "stt_demo = gr.load(\n", " \"huggingface/facebook/wav2vec2-base-960h\",\n", " title=None,\n", " inputs=gr.Microphone(type=\"filepath\"),\n", " description=\"Let me try to guess what you're saying!\",\n", ")\n", "\n", "demo = gr.TabbedInterface([tts_demo, stt_demo], [\"Text-to-speech\", \"Speech-to-text\"])\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} \ No newline at end of file diff --git a/demos/stt_or_tts/run.py b/demos/stt_or_tts/run.py new file mode 100644 index 0000000000000000000000000000000000000000..e364cba3e7b42c0965d751e2aa3bf3999445c041 --- /dev/null +++ b/demos/stt_or_tts/run.py @@ -0,0 +1,25 @@ +import gradio as gr + +tts_examples = [ + "I love learning machine learning", + "How do you do?", +] + +tts_demo = gr.load( + "huggingface/facebook/fastspeech2-en-ljspeech", + title=None, + examples=tts_examples, + description="Give me something to say!", +) + +stt_demo = gr.load( + "huggingface/facebook/wav2vec2-base-960h", + title=None, + inputs=gr.Microphone(type="filepath"), + description="Let me try to guess what you're saying!", +) + +demo = gr.TabbedInterface([tts_demo, stt_demo], ["Text-to-speech", "Speech-to-text"]) + +if __name__ == "__main__": + demo.launch() diff --git a/demos/video_component/files/a.mp4 b/demos/video_component/files/a.mp4 new file mode 100644 index 0000000000000000000000000000000000000000..95a61f6b4a753497d97f51c6a8f18727cef7d628 Binary files /dev/null and b/demos/video_component/files/a.mp4 differ diff --git a/demos/video_component/files/b.mp4 b/demos/video_component/files/b.mp4 new file mode 100644 index 0000000000000000000000000000000000000000..7b2d7c723ea53ce763eb49f551bd955858850673 Binary files /dev/null and b/demos/video_component/files/b.mp4 differ diff --git a/demos/video_component/files/world.mp4 b/demos/video_component/files/world.mp4 new file mode 100644 index 0000000000000000000000000000000000000000..9bce44c33e275d6107240a1101032a7835fd8eed --- /dev/null +++ b/demos/video_component/files/world.mp4 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:71944d7430c461f0cd6e7fd10cee7eb72786352a3678fc7bc0ae3d410f72aece +size 1570024 diff --git a/demos/video_component/run.ipynb b/demos/video_component/run.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..4387ae475020ca1e702948345ee0ebd37d640315 --- /dev/null +++ b/demos/video_component/run.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: video_component"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "os.mkdir('files')\n", "!wget -q -O files/a.mp4 https://github.com/gradio-app/gradio/raw/main/demo/video_component/files/a.mp4\n", "!wget -q -O files/b.mp4 https://github.com/gradio-app/gradio/raw/main/demo/video_component/files/b.mp4\n", "!wget -q -O files/world.mp4 https://github.com/gradio-app/gradio/raw/main/demo/video_component/files/world.mp4"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import os\n", "\n", "\n", "a = os.path.join(os.path.abspath(''), \"files/world.mp4\") # Video\n", "b = os.path.join(os.path.abspath(''), \"files/a.mp4\") # Video\n", "c = os.path.join(os.path.abspath(''), \"files/b.mp4\") # Video\n", "\n", "\n", "demo = gr.Interface(\n", " fn=lambda x: x,\n", " inputs=gr.Video(),\n", " outputs=gr.Video(),\n", " examples=[\n", " [a],\n", " [b],\n", " [c],\n", " ],\n", " cache_examples=True\n", ")\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} \ No newline at end of file diff --git a/demos/video_component/run.py b/demos/video_component/run.py new file mode 100644 index 0000000000000000000000000000000000000000..d522aa49cdcff3e53341f0b5d8d7122ad90779ba --- /dev/null +++ b/demos/video_component/run.py @@ -0,0 +1,23 @@ +import gradio as gr +import os + + +a = os.path.join(os.path.dirname(__file__), "files/world.mp4") # Video +b = os.path.join(os.path.dirname(__file__), "files/a.mp4") # Video +c = os.path.join(os.path.dirname(__file__), "files/b.mp4") # Video + + +demo = gr.Interface( + fn=lambda x: x, + inputs=gr.Video(), + outputs=gr.Video(), + examples=[ + [a], + [b], + [c], + ], + cache_examples=True +) + +if __name__ == "__main__": + demo.launch() diff --git a/demos/zip_files/.gitignore b/demos/zip_files/.gitignore new file mode 100644 index 0000000000000000000000000000000000000000..8e9b8f2027a5cfe97c8c9c96709fc2453c0df220 --- /dev/null +++ b/demos/zip_files/.gitignore @@ -0,0 +1 @@ +tmp.zip \ No newline at end of file diff --git a/demos/zip_files/files/titanic.csv b/demos/zip_files/files/titanic.csv new file mode 100644 index 0000000000000000000000000000000000000000..63b68ab0ba98c667f515c52f08c0bbd5573d5330 --- /dev/null +++ b/demos/zip_files/files/titanic.csv @@ -0,0 +1,892 @@ +PassengerId,Survived,Pclass,Name,Sex,Age,SibSp,Parch,Ticket,Fare,Cabin,Embarked +1,0,3,"Braund, Mr. Owen Harris",male,22,1,0,A/5 21171,7.25,,S +2,1,1,"Cumings, Mrs. John Bradley (Florence Briggs Thayer)",female,38,1,0,PC 17599,71.2833,C85,C +3,1,3,"Heikkinen, Miss. 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Catherine Helen ""Carrie""",female,,1,2,W./C. 6607,23.45,,S +890,1,1,"Behr, Mr. Karl Howell",male,26,0,0,111369,30,C148,C +891,0,3,"Dooley, Mr. Patrick",male,32,0,0,370376,7.75,,Q diff --git a/demos/zip_files/run.ipynb b/demos/zip_files/run.ipynb new file mode 100644 index 0000000000000000000000000000000000000000..a2732e7f190d2ae4a542cf615a6105d59f904aa9 --- /dev/null +++ b/demos/zip_files/run.ipynb @@ -0,0 +1 @@ +{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: zip_files"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "os.mkdir('files')\n", "!wget -q -O files/titanic.csv https://github.com/gradio-app/gradio/raw/main/demo/zip_files/files/titanic.csv"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import os\n", "from zipfile import ZipFile\n", "\n", "import gradio as gr\n", "\n", "\n", "def zip_files(files):\n", " with ZipFile(\"tmp.zip\", \"w\") as zipObj:\n", " for idx, file in enumerate(files):\n", " zipObj.write(file.name, file.name.split(\"/\")[-1])\n", " return \"tmp.zip\"\n", "\n", "demo = gr.Interface(\n", " zip_files,\n", " gr.File(file_count=\"multiple\", file_types=[\"text\", \".json\", \".csv\"]),\n", " \"file\",\n", " examples=[[[os.path.join(os.path.abspath(''),\"files/titanic.csv\"), \n", " os.path.join(os.path.abspath(''),\"files/titanic.csv\"), \n", " os.path.join(os.path.abspath(''),\"files/titanic.csv\")]]], \n", " cache_examples=True\n", ")\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} \ No newline at end of file diff --git a/demos/zip_files/run.py b/demos/zip_files/run.py new file mode 100644 index 0000000000000000000000000000000000000000..1ae6436c67542f82a94ca7c6d9675974b2503710 --- /dev/null +++ b/demos/zip_files/run.py @@ -0,0 +1,24 @@ +import os +from zipfile import ZipFile + +import gradio as gr + + +def zip_files(files): + with ZipFile("tmp.zip", "w") as zipObj: + for idx, file in enumerate(files): + zipObj.write(file.name, file.name.split("/")[-1]) + return "tmp.zip" + +demo = gr.Interface( + zip_files, + gr.File(file_count="multiple", file_types=["text", ".json", ".csv"]), + "file", + examples=[[[os.path.join(os.path.dirname(__file__),"files/titanic.csv"), + os.path.join(os.path.dirname(__file__),"files/titanic.csv"), + os.path.join(os.path.dirname(__file__),"files/titanic.csv")]]], + cache_examples=True +) + +if __name__ == "__main__": + demo.launch() diff --git a/demos/zip_files/screenshot.png b/demos/zip_files/screenshot.png new file mode 100644 index 0000000000000000000000000000000000000000..64591ff8a23e8c77759f60f7caddc61fb84f3324 Binary files /dev/null and b/demos/zip_files/screenshot.png differ diff --git a/image.png b/image.png new file mode 100644 index 0000000000000000000000000000000000000000..dc392ea95476974e07a68ad98a9659c240e1089b Binary files /dev/null and b/image.png differ diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 0000000000000000000000000000000000000000..6785c30eda65924caa7185d2534f08845beaedf6 --- /dev/null +++ b/requirements.txt @@ -0,0 +1,10 @@ + +gradio-client @ git+https://github.com/gradio-app/gradio@ac7f611012042e97ba881d640a76d26b6f8e7dc4#subdirectory=client/python +https://gradio-builds.s3.amazonaws.com/ac7f611012042e97ba881d640a76d26b6f8e7dc4/gradio-4.32.0-py3-none-any.whl +pypistats==1.1.0 +plotly==5.10.0 +opencv-python==4.6.0.66 +transformers==4.21.1 +torch==1.12.1 +altair +vega_datasets diff --git a/templates/index.html b/templates/index.html new file mode 100644 index 0000000000000000000000000000000000000000..3eef8da37e6796a02af89cf666bbbe0b733a6079 --- /dev/null +++ b/templates/index.html @@ -0,0 +1,118 @@ + + + + {%if is_space %} + + {% endif %} + + + + +
+
+ +
+
+ {% for name in names %} + {{ name[0] }} {% if name[1] %}❌{% endif %} + {% endfor %} +
+
+
+ +
+ + \ No newline at end of file