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Runtime error
roobsis
commited on
Commit
·
3d03641
1
Parent(s):
fd42824
updated to work on huggingface
Browse files
.DS_Store
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Binary file (6.15 kB). View file
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app.py
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@@ -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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import gradio as gr
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from fastai.vision.all import *
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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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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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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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myinterface = gr.Interface(fn = classify_image,inputs = image,outputs = label, examples = examples)
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myinterface.launch (inline=False)
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elf.ipynb
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@@ -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":
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"metadata": {},
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"outputs": [
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{
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"
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"
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"
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"\
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"
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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": [
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@@ -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": {},
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},
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{
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"cell_type": "code",
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"execution_count":
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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": "
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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": "
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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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},
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tiefling.jpg
ADDED