{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/mks/.local/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
" from .autonotebook import tqdm as notebook_tqdm\n"
]
}
],
"source": [
"%load_ext gradio"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Running on local URL: http://127.0.0.1:7860\n"
]
},
{
"data": {
"text/html": [
""
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%%blocks \n",
"\n",
"import gradio as gr\n",
"\n",
"gr.Markdown(\"# Greetings from Gradio!\")\n",
"inp = gr.Textbox(placeholder=\"What is your name?\")\n",
"out = gr.Textbox()\n",
"\n",
"inp.change(fn=lambda x: f\"Welcome, {x}!\", \n",
" inputs=inp, \n",
" outputs=out)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/mks/.local/lib/python3.10/site-packages/gradio/ipython_ext.py:18: UserWarning: Usage of gradio.Interface with %%blocks may result in errors.\n",
" warnings.warn(\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Running on local URL: http://127.0.0.1:7861\n",
"\n",
"To create a public link, set `share=True` in `launch()`.\n"
]
},
{
"data": {
"text/html": [
""
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Running on local URL: http://127.0.0.1:7860\n"
]
},
{
"data": {
"text/html": [
""
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%%blocks \n",
"def greet(name):\n",
" return \"Hello \" + name + \"!\"\n",
"\n",
"demo = gr.Interface(fn=greet, inputs=\"text\", outputs=\"text\")\n",
" \n",
"demo.launch() "
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Running on local URL: http://127.0.0.1:7863\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": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import gradio as gr\n",
"\n",
"def greet(name):\n",
" return \"Hello \" + name + \"!\"\n",
"\n",
"demo = gr.Interface(\n",
" fn=greet,\n",
" inputs=gr.Textbox(lines=4, placeholder=\"Name Here...\"),\n",
" outputs=\"text\",\n",
")\n",
"demo.launch()"
]
},
{
"cell_type": "code",
"execution_count": 15,
"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": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import gradio as gr\n",
"\n",
"def greet(yourname, is_morning, temperature):\n",
" salutation = \"Good morning\" if is_morning else \"Good evening\"\n",
" greeting = f\"{salutation} {name}. It is {temperature} degrees Fahrenheit today.\"\n",
" celsius = (temperature - 32) * 5 / 9\n",
" return greeting, round(celsius, 2)\n",
"\n",
"demo = gr.Interface(\n",
" fn=greet,\n",
" inputs=[\"text\", \"checkbox\", gr.Slider(-50, 100)],\n",
" outputs=[\"text\", \"number\"],\n",
")\n",
"demo.launch()"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Running on local URL: http://127.0.0.1:7870\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": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import numpy as np\n",
"import gradio as gr\n",
"\n",
"def sepia(input_img):\n",
" sepia_filter = np.array([\n",
" [0.393, 0.769, 0.189], \n",
" [0.349, 0.686, 0.168], \n",
" [0.272, 0.534, 0.131]\n",
" ])\n",
" sepia_img = input_img.dot(sepia_filter.T)\n",
" sepia_img /= sepia_img.max()\n",
" return sepia_img\n",
"\n",
"demo = gr.Interface(sepia, gr.Image(shape=(200, 200)), \"image\")\n",
"demo.launch()"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Running on local URL: http://127.0.0.1:7871\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": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import gradio as gr\n",
"\n",
"def greet(name):\n",
" return \"Hello \" + name + \"!\"\n",
"\n",
"with gr.Blocks() as demo:\n",
" name = gr.Textbox(label=\"Name\")\n",
" output = gr.Textbox(label=\"Output Box\")\n",
" greet_btn = gr.Button(\"Greet\")\n",
" greet_btn.click(fn=greet, inputs=name, outputs=output, api_name=\"greet\")\n",
"\n",
"demo.launch()"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Running on local URL: http://127.0.0.1:7872\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": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import numpy as np\n",
"import gradio as gr\n",
"\n",
"\n",
"def flip_text(x):\n",
" return x[::-1]\n",
"\n",
"\n",
"def flip_image(x):\n",
" return np.fliplr(x)\n",
"\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!\"):\n",
" gr.Markdown(\"Look at me...\")\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",
"demo.launch()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"! pip install nbconvert -U"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[NbConvertApp] Converting notebook app.ipynb to script\n",
"[NbConvertApp] Writing 2888 bytes to app.py\n"
]
}
],
"source": [
"!jupyter nbconvert --to script app.ipynb"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.10.6"
},
"orig_nbformat": 4
},
"nbformat": 4,
"nbformat_minor": 2
}