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Browse files- README.md +1 -1
- requirements.txt +1 -0
- run.ipynb +1 -1
README.md
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sdk: gradio
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sdk_version:
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app_file: run.py
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hf_oauth: true
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sdk: gradio
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sdk_version: 5.0.0
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app_file: run.py
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requirements.txt
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numpy
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run.ipynb
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{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: blocks_flipper"]}, {"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", "import gradio as gr\n", "\n", "def flip_text(x):\n", " return x[::-1]\n", "\n", "def flip_image(x):\n", " return np.fliplr(x)\n", "\n", "with gr.Blocks() as demo:\n", " gr.Markdown(\"Flip text or image files using this demo.\")\n", " with gr.Tab(\"Flip Text\"):\n", " text_input = gr.Textbox()\n", " text_output = gr.Textbox()\n", " text_button = gr.Button(\"Flip\")\n", " with gr.Tab(\"Flip Image\"):\n", " with gr.Row():\n", " image_input = gr.Image()\n", " image_output = gr.Image()\n", " image_button = gr.Button(\"Flip\")\n", "\n", " with gr.Accordion(\"Open for More!\", open=False):\n", " gr.Markdown(\"Look at me...\")\n", " temp_slider = gr.Slider(\n", " 0, 1,\n", " value=0.1,\n", " step=0.1,\n", " interactive=True,\n", " label=\"Slide me\",\n", " )\n", "\n", " text_button.click(flip_text, inputs=text_input, outputs=text_output)\n", " image_button.click(flip_image, inputs=image_input, outputs=image_output)\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
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{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: blocks_flipper"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio numpy "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import numpy as np\n", "import gradio as gr\n", "\n", "def flip_text(x):\n", " return x[::-1]\n", "\n", "def flip_image(x):\n", " return np.fliplr(x)\n", "\n", "with gr.Blocks() as demo:\n", " gr.Markdown(\"Flip text or image files using this demo.\")\n", " with gr.Tab(\"Flip Text\"):\n", " text_input = gr.Textbox()\n", " text_output = gr.Textbox()\n", " text_button = gr.Button(\"Flip\")\n", " with gr.Tab(\"Flip Image\"):\n", " with gr.Row():\n", " image_input = gr.Image()\n", " image_output = gr.Image()\n", " image_button = gr.Button(\"Flip\")\n", "\n", " with gr.Accordion(\"Open for More!\", open=False):\n", " gr.Markdown(\"Look at me...\")\n", " temp_slider = gr.Slider(\n", " 0, 1,\n", " value=0.1,\n", " step=0.1,\n", " interactive=True,\n", " label=\"Slide me\",\n", " )\n", "\n", " text_button.click(flip_text, inputs=text_input, outputs=text_output)\n", " image_button.click(flip_image, inputs=image_input, outputs=image_output)\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
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