{
"cells": [
{
"cell_type": "code",
"execution_count": 92,
"metadata": {},
"outputs": [],
"source": [
"#|default_exp app"
]
},
{
"cell_type": "code",
"execution_count": 93,
"metadata": {},
"outputs": [],
"source": [
"#|export\n",
"from fastai.vision.all import *\n",
"import gradio as gr\n",
"\n",
"def is_man(x): return x[0].isupper()"
]
},
{
"cell_type": "code",
"execution_count": 94,
"metadata": {},
"outputs": [],
"source": [
"girl1 = PILImage.create('/Users/francostratta/Desktop/learning/girl1.jpeg')\n",
"girl2 = PILImage.create('/Users/francostratta/Desktop/learning/girl2.jpg')\n",
"girl3 = PILImage.create('/Users/francostratta/Desktop/learning/girl3.jpg')\n",
"\n",
"man1 = PILImage.create('/Users/francostratta/Desktop/learning/man1.jpeg')\n",
"man2 = PILImage.create('/Users/francostratta/Desktop/learning/man2.jpg')\n",
"man3 = PILImage.create('/Users/francostratta/Desktop/learning/man3.jpg')"
]
},
{
"cell_type": "code",
"execution_count": 95,
"metadata": {},
"outputs": [],
"source": [
"#|export\n",
"learn = load_learner('sex.pkl')"
]
},
{
"cell_type": "code",
"execution_count": 96,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"('women', tensor(1), tensor([6.9461e-05, 9.9993e-01]))"
]
},
"execution_count": 96,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"learn.predict(girl1)"
]
},
{
"cell_type": "code",
"execution_count": 97,
"metadata": {},
"outputs": [],
"source": [
"#|export\n",
"categories = (\"man\", \"girl\")\n",
"\n",
"def classify_image(img):\n",
" pred, idx, probs = learn.predict(img)\n",
" return dict(zip(categories, map(float,probs)))"
]
},
{
"cell_type": "code",
"execution_count": 98,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"girl1: {'man': 6.946067151147872e-05, 'girl': 0.9999305009841919}\n"
]
},
{
"data": {
"text/html": [
"\n",
"\n"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"man1: {'man': 0.9999998807907104, 'girl': 1.692434494771078e-07}\n"
]
}
],
"source": [
"print('girl1: ',classify_image(girl1))\n",
"print('man1: ',classify_image(man1))"
]
},
{
"cell_type": "code",
"execution_count": 99,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Running on local URL: http://127.0.0.1:7869\n",
"\n",
"To create a public link, set `share=True` in `launch()`.\n"
]
},
{
"data": {
"text/html": [
""
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": []
},
"execution_count": 99,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#|export\n",
"Image = gr.Image()\n",
"label = gr.Label()\n",
"examples = ['girl1.jpeg', 'man1.jpeg']\n",
"\n",
"interface = gr.Interface(\n",
" fn=classify_image,\n",
" inputs=Image,\n",
" outputs=label,\n",
" examples=examples)\n",
"\n",
"interface.launch()"
]
},
{
"cell_type": "code",
"execution_count": 100,
"metadata": {},
"outputs": [],
"source": [
"!nbdev_migrate "
]
},
{
"cell_type": "code",
"execution_count": 101,
"metadata": {},
"outputs": [],
"source": [
"import nbdev\n",
"nbdev.export.nb_export('app.ipynb', '.')\n"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "base",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.8"
}
},
"nbformat": 4,
"nbformat_minor": 2
}