Spaces:
Sleeping
Sleeping
李根赢
commited on
Commit
•
1335d7c
1
Parent(s):
038a1fb
add app.py
Browse files- .ipynb_checkpoints/app-checkpoint.ipynb +82 -0
- app.ipynb +140 -0
- app.py +16 -4
- bear.jpg +0 -0
- export.pkl +3 -0
.ipynb_checkpoints/app-checkpoint.ipynb
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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": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# /default_exp app"
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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": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# export\n",
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"from fastai.vision.all import *\n",
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"import gradio as gr"
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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": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"learn = load_learner('model.pkl')"
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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": null,
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"metadata": {},
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"outputs": [],
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"source": []
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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": []
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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": []
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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": []
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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": []
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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": []
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}
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],
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"metadata": {
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"language_info": {
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"name": "python"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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app.ipynb
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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": 7,
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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 'fastbook'",
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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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"\u001b[1;32m/home/ghost/pythoncode/bear_classifier/app.ipynb Cell 1\u001b[0m line \u001b[0;36m2\n\u001b[1;32m <a href='vscode-notebook-cell:/home/ghost/pythoncode/bear_classifier/app.ipynb#W0sZmlsZQ%3D%3D?line=0'>1</a>\u001b[0m get_ipython()\u001b[39m.\u001b[39msystem(\u001b[39m'\u001b[39m\u001b[39m [ -e /content ] && pip install -Uqq fastbook\u001b[39m\u001b[39m'\u001b[39m)\n\u001b[0;32m----> <a href='vscode-notebook-cell:/home/ghost/pythoncode/bear_classifier/app.ipynb#W0sZmlsZQ%3D%3D?line=1'>2</a>\u001b[0m \u001b[39mimport\u001b[39;00m \u001b[39mfastbook\u001b[39;00m\n\u001b[1;32m <a href='vscode-notebook-cell:/home/ghost/pythoncode/bear_classifier/app.ipynb#W0sZmlsZQ%3D%3D?line=2'>3</a>\u001b[0m fastbook\u001b[39m.\u001b[39msetup_book()\n\u001b[1;32m <a href='vscode-notebook-cell:/home/ghost/pythoncode/bear_classifier/app.ipynb#W0sZmlsZQ%3D%3D?line=4'>5</a>\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mfastbook\u001b[39;00m \u001b[39mimport\u001b[39;00m \u001b[39m*\u001b[39m\n",
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"\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'fastbook'"
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]
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}
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],
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"source": [
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"! [ -e /content ] && pip install -Uqq fastbook\n",
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"import fastbook\n",
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"fastbook.setup_book()\n",
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"\n",
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"from fastbook import *\n",
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"from fastai.vision.widgets import *"
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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": 5,
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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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"\u001b[KFatal error from pip prevented installation. Full pip output in file:\n",
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" /home/ghost/.local/pipx/logs/cmd_2024-03-08_10.04.53_pip_errors.log\n",
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"\n",
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"Some possibly relevant errors from pip install:\n",
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" \u001b[0m\u001b[31mERROR: Could not find a version that satisfies the requirement gradio (from versions: none)\u001b[0m\u001b[31m\n",
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" \u001b[0m\u001b[31mERROR: No matching distribution found for gradio\u001b[0m\u001b[31m\n",
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"\n",
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"Error installing gradio.\n",
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"\u001b[?25h\u001b[0m"
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]
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},
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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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"\u001b[1;32m/home/ghost/pythoncode/bear_classifier/app.ipynb Cell 2\u001b[0m line \u001b[0;36m3\n\u001b[1;32m <a href='vscode-notebook-cell:/home/ghost/pythoncode/bear_classifier/app.ipynb#W1sZmlsZQ%3D%3D?line=0'>1</a>\u001b[0m \u001b[39m# export\u001b[39;00m\n\u001b[1;32m <a href='vscode-notebook-cell:/home/ghost/pythoncode/bear_classifier/app.ipynb#W1sZmlsZQ%3D%3D?line=1'>2</a>\u001b[0m get_ipython()\u001b[39m.\u001b[39msystem(\u001b[39m'\u001b[39m\u001b[39m pipx install gradio\u001b[39m\u001b[39m'\u001b[39m)\n\u001b[0;32m----> <a href='vscode-notebook-cell:/home/ghost/pythoncode/bear_classifier/app.ipynb#W1sZmlsZQ%3D%3D?line=2'>3</a>\u001b[0m \u001b[39mimport\u001b[39;00m \u001b[39mgradio\u001b[39;00m \u001b[39mas\u001b[39;00m \u001b[39mgr\u001b[39;00m\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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"# export\n",
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"! pipx install gradio\n",
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"import gradio as gr"
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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": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"learn = load_learner('model.pkl')"
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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": null,
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"metadata": {},
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"outputs": [],
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"source": []
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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": []
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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": []
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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": []
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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": []
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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": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.8"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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app.py
CHANGED
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import gradio as gr
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# AUTOGENERATED! DO NOT EDIT! File to edit: gdrive/MyDrive/Colab Notebooks/Untitled8.ipynb.
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# %% auto 0
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__all__ = ['path', 'learn_inf', 'btn_upload', 'pred', 'pred_idx', 'probs']
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# %% gdrive/MyDrive/Colab Notebooks/Untitled8.ipynb 24
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from fastai.vision.widgets import *
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import gradio as gr
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# %% gdrive/MyDrive/Colab Notebooks/Untitled8.ipynb 25
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# path = Path('bears')
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learn_inf = load_learner('export.pkl')
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# %% gdrive/MyDrive/Colab Notebooks/Untitled8.ipynb 26
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btn_upload = widgets.FileUpload()
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btn_upload
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# %% gdrive/MyDrive/Colab Notebooks/Untitled8.ipynb 30
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pred,pred_idx,probs = learn_inf.predict(img)
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bear.jpg
ADDED
export.pkl
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:64fcc399f6556d2c54c26d69344310010ac3d9a024b9926fb0bf1a5838eade6d
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size 46969470
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