roobsis commited on
Commit
3d03641
·
1 Parent(s): fd42824

updated to work on huggingface

Browse files
Files changed (4) hide show
  1. .DS_Store +0 -0
  2. app.py +19 -4
  3. elf.ipynb +67 -12
  4. tiefling.jpg +0 -0
.DS_Store ADDED
Binary file (6.15 kB). View file
 
app.py CHANGED
@@ -1,7 +1,22 @@
 
 
 
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  import gradio as gr
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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- def greet(name):
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- return "Hello " + name + "!!"
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- iface = gr.Interface(fn=greet, inputs="text", outputs="text")
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- iface.launch()
 
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+ __all__ = ['learn','classify_image','categories','image','label','examples','myinterface']
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+
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+
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  import gradio as gr
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+ from fastai.vision.all import *
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+
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+ learn = load_learner('elf_export.pkl')
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+ categories = ('dragonborne','dwarf','elf','halfling','human','tiefling')
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+
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+ def classify_image (img):
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+ pred,idx,probs = learn.predict(img)
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+ return dict(zip(categories,map(float,probs)))
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+
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+ image = gr.inputs.Image (shape = (192,192))
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+ label = gr.outputs.Label ()
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+ examples = ['tiefling.jpg']
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+
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+ myinterface = gr.Interface(fn = classify_image,inputs = image,outputs = label, examples = examples)
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+ myinterface.launch (inline=False)
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+
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elf.ipynb CHANGED
@@ -2,19 +2,37 @@
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  "cells": [
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  {
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  "cell_type": "code",
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- "execution_count": 1,
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  "metadata": {},
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  "outputs": [
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  {
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- "ename": "ModuleNotFoundError",
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- "evalue": "No module named 'gradio'",
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- "output_type": "error",
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- "traceback": [
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- "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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- "\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)",
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- "Cell \u001b[0;32mIn[1], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[39mimport\u001b[39;00m \u001b[39mgradio\u001b[39;00m \u001b[39mas\u001b[39;00m \u001b[39mgr\u001b[39;00m\n\u001b[1;32m 3\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mgreet\u001b[39m(name):\n\u001b[1;32m 4\u001b[0m \u001b[39mreturn\u001b[39;00m \u001b[39m\"\u001b[39m\u001b[39mHello \u001b[39m\u001b[39m\"\u001b[39m \u001b[39m+\u001b[39m name \u001b[39m+\u001b[39m \u001b[39m\"\u001b[39m\u001b[39m!!\u001b[39m\u001b[39m\"\u001b[39m\n",
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- "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'gradio'"
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  ]
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  }
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  ],
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  "source": [
@@ -27,6 +45,43 @@
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  "iface.launch()"
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  ]
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  },
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  {
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  "cell_type": "markdown",
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  "metadata": {},
@@ -34,7 +89,7 @@
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  },
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  {
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  "cell_type": "code",
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- "execution_count": null,
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  "metadata": {},
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  "outputs": [],
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  "source": [
@@ -44,7 +99,7 @@
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  ],
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  "metadata": {
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  "kernelspec": {
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- "display_name": "Python 3",
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  "language": "python",
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  "name": "python3"
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  },
@@ -63,7 +118,7 @@
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  "orig_nbformat": 4,
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  "vscode": {
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  "interpreter": {
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- "hash": "31f2aee4e71d21fbe5cf8b01ff0e069b9275f58929596ceb00d14d90e3e16cd6"
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  }
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  }
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  },
 
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  "cells": [
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  {
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  "cell_type": "code",
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+ "execution_count": 3,
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  "metadata": {},
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  "outputs": [
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  {
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+ "name": "stdout",
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+ "output_type": "stream",
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+ "text": [
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+ "Running on local URL: http://127.0.0.1:7860\n",
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+ "\n",
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+ "To create a public link, set `share=True` in `launch()`.\n"
 
 
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  ]
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+ },
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+ {
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+ "data": {
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+ "text/html": [
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+ "<div><iframe src=\"http://127.0.0.1:7860/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
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+ ],
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+ "text/plain": [
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+ "<IPython.core.display.HTML object>"
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+ ]
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+ },
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+ "metadata": {},
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+ "output_type": "display_data"
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+ },
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+ {
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+ "data": {
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+ "text/plain": []
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+ },
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+ "execution_count": 3,
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+ "metadata": {},
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+ "output_type": "execute_result"
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  }
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  ],
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  "source": [
 
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  "iface.launch()"
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  ]
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  },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 4,
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+ "metadata": {},
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+ "outputs": [
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+ {
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+ "data": {
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+ "text/html": [],
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+ "text/plain": [
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+ "<IPython.core.display.HTML object>"
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+ ]
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+ },
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+ "metadata": {},
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+ "output_type": "display_data"
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+ },
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+ {
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+ "data": {
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+ "text/plain": [
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+ "('elf',\n",
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+ " TensorBase(2),\n",
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+ " TensorBase([2.4853e-03, 4.2622e-03, 9.9193e-01, 1.0128e-03, 2.4441e-04,\n",
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+ " 6.5845e-05]))"
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+ ]
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+ },
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+ "execution_count": 4,
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+ "metadata": {},
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+ "output_type": "execute_result"
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+ }
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+ ],
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+ "source": [
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+ "import gradio as gr\n",
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+ "from fastai.vision.all import *\n",
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+ "\n",
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+ "learn = load_learner('elf_export.pkl')\n",
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+ "learn.predict ('tiefling.jpg')"
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+ ]
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+ },
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  {
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  "cell_type": "markdown",
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  "metadata": {},
 
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  },
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  {
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  "cell_type": "code",
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+ "execution_count": 2,
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  "metadata": {},
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  "outputs": [],
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  "source": [
 
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  ],
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  "metadata": {
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  "kernelspec": {
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+ "display_name": ".venv",
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  "language": "python",
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  "name": "python3"
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  },
 
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  "orig_nbformat": 4,
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  "vscode": {
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  "interpreter": {
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+ "hash": "25613e3f86799f8fc5e212a950c5421386eb1419de4db49b5cf413f9a619b293"
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  }
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  }
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  },
tiefling.jpg ADDED