Undo notebooks

Author: freddyaboulton

demo/blocks_inputs/run.ipynb

@@ -1 +1 @@
-{"cells": [{"cell_type": "markdown", "id": 302934307671667531413257853548643485645, "metadata": {}, "source": ["# Gradio Demo: blocks_inputs"]}, {"cell_type": "code", "execution_count": null, "id": 272996653310673477252411125948039410165, "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": 288918539441861185822528903084949547379, "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/blocks_inputs/config.json\n", "os.mkdir('gradio_cached_examples')\n", "!wget -q -O gradio_cached_examples/10 https://github.com/gradio-app/gradio/raw/main/demo/blocks_inputs/gradio_cached_examples/10\n", "!wget -q -O gradio_cached_examples/12 https://github.com/gradio-app/gradio/raw/main/demo/blocks_inputs/gradio_cached_examples/12\n", "!wget -q -O gradio_cached_examples/18 https://github.com/gradio-app/gradio/raw/main/demo/blocks_inputs/gradio_cached_examples/18\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/blocks_inputs/lion.jpg"]}, {"cell_type": "code", "execution_count": null, "id": 44380577570523278879349135829904343037, "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import os\n", "\n", "\n", "def combine(a, b):\n", "    return a + \" \" + b\n", "\n", "\n", "def mirror(x):\n", "    return x\n", "\n", "\n", "with gr.Blocks() as demo:\n", "\n", "    txt = gr.Textbox(label=\"Input\", lines=2)\n", "    txt_2 = gr.Textbox(label=\"Input 2\")\n", "    txt_3 = gr.Textbox(value=\"\", label=\"Output\")\n", "    btn = gr.Button(value=\"Submit\")\n", "    btn.click(combine, inputs=[txt, txt_2], outputs=[txt_3])\n", "\n", "    with gr.Row():\n", "        im = gr.Image()\n", "        im_2 = gr.Image()\n", "\n", "    btn = gr.Button(value=\"Mirror Image\")\n", "    btn.click(mirror, inputs=[im], outputs=[im_2])\n", "\n", "    gr.Markdown(\"## Text Examples\")\n", "    gr.Examples(\n", "        [[\"hi\", \"Adam\"], [\"hello\", \"Eve\"]],\n", "        [txt, txt_2],\n", "        txt_3,\n", "        combine,\n", "        cache_examples=True,\n", "    )\n", "    gr.Markdown(\"## Image Examples\")\n", "    gr.Examples(\n", "        examples=[os.path.join(os.path.abspath(''), \"lion.jpg\")],\n", "        inputs=im,\n", "        outputs=im_2,\n", "        fn=mirror,\n", "        cache_examples=True,\n", "    )\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
+{"cells": [{"cell_type": "markdown", "id": 302934307671667531413257853548643485645, "metadata": {}, "source": ["# Gradio Demo: blocks_inputs"]}, {"cell_type": "code", "execution_count": null, "id": 272996653310673477252411125948039410165, "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": 288918539441861185822528903084949547379, "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/blocks_inputs/lion.jpg"]}, {"cell_type": "code", "execution_count": null, "id": 44380577570523278879349135829904343037, "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import os\n", "\n", "\n", "def combine(a, b):\n", "    return a + \" \" + b\n", "\n", "\n", "def mirror(x):\n", "    return x\n", "\n", "\n", "with gr.Blocks() as demo:\n", "\n", "    txt = gr.Textbox(label=\"Input\", lines=2)\n", "    txt_2 = gr.Textbox(label=\"Input 2\")\n", "    txt_3 = gr.Textbox(value=\"\", label=\"Output\")\n", "    btn = gr.Button(value=\"Submit\")\n", "    btn.click(combine, inputs=[txt, txt_2], outputs=[txt_3])\n", "\n", "    with gr.Row():\n", "        im = gr.Image()\n", "        im_2 = gr.Image()\n", "\n", "    btn = gr.Button(value=\"Mirror Image\")\n", "    btn.click(mirror, inputs=[im], outputs=[im_2])\n", "\n", "    gr.Markdown(\"## Text Examples\")\n", "    gr.Examples(\n", "        [[\"hi\", \"Adam\"], [\"hello\", \"Eve\"]],\n", "        [txt, txt_2],\n", "        txt_3,\n", "        combine,\n", "        cache_examples=True,\n", "    )\n", "    gr.Markdown(\"## Image Examples\")\n", "    gr.Examples(\n", "        examples=[os.path.join(os.path.abspath(''), \"lion.jpg\")],\n", "        inputs=im,\n", "        outputs=im_2,\n", "        fn=mirror,\n", "        cache_examples=True,\n", "    )\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

demo/blocks_kinematics/run.ipynb

@@ -1 +1 @@
-{"cells": [{"cell_type": "markdown", "id": 302934307671667531413257853548643485645, "metadata": {}, "source": ["# Gradio Demo: blocks_kinematics"]}, {"cell_type": "code", "execution_count": null, "id": 272996653310673477252411125948039410165, "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": 288918539441861185822528903084949547379, "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/blocks_kinematics/config.json"]}, {"cell_type": "code", "execution_count": null, "id": 44380577570523278879349135829904343037, "metadata": {}, "outputs": [], "source": ["import matplotlib\n", "matplotlib.use('Agg')\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "\n", "import gradio as gr\n", "\n", "\n", "def plot(v, a):\n", "    g = 9.81\n", "    theta = a / 180 * 3.14\n", "    tmax = ((2 * v) * np.sin(theta)) / g\n", "    timemat = tmax * np.linspace(0, 1, 40)[:, None]\n", "\n", "    x = (v * timemat) * np.cos(theta)\n", "    y = ((v * timemat) * np.sin(theta)) - ((0.5 * g) * (timemat**2))\n", "\n", "    fig = plt.figure()\n", "    plt.scatter(x=x, y=y, marker=\".\")\n", "    plt.xlim(0, 100)\n", "    plt.ylim(0, 60)\n", "    return fig\n", "\n", "\n", "demo = gr.Blocks()\n", "\n", "with demo:\n", "    gr.Markdown(\n", "        r\"Let's do some kinematics! Choose the speed and angle to see the trajectory. Remember that the range $R = v_0^2 \\cdot \\frac{\\sin(2\\theta)}{g}$\"\n", "    )\n", "\n", "    with gr.Row():\n", "        speed = gr.Slider(1, 30, 25, label=\"Speed\")\n", "        angle = gr.Slider(0, 90, 45, label=\"Angle\")\n", "    output = gr.Plot()\n", "    btn = gr.Button(value=\"Run\")\n", "    btn.click(plot, [speed, angle], output)\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
+{"cells": [{"cell_type": "markdown", "id": 302934307671667531413257853548643485645, "metadata": {}, "source": ["# Gradio Demo: blocks_kinematics"]}, {"cell_type": "code", "execution_count": null, "id": 272996653310673477252411125948039410165, "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": 288918539441861185822528903084949547379, "metadata": {}, "outputs": [], "source": ["import matplotlib\n", "matplotlib.use('Agg')\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "\n", "import gradio as gr\n", "\n", "\n", "def plot(v, a):\n", "    g = 9.81\n", "    theta = a / 180 * 3.14\n", "    tmax = ((2 * v) * np.sin(theta)) / g\n", "    timemat = tmax * np.linspace(0, 1, 40)[:, None]\n", "\n", "    x = (v * timemat) * np.cos(theta)\n", "    y = ((v * timemat) * np.sin(theta)) - ((0.5 * g) * (timemat**2))\n", "\n", "    fig = plt.figure()\n", "    plt.scatter(x=x, y=y, marker=\".\")\n", "    plt.xlim(0, 100)\n", "    plt.ylim(0, 60)\n", "    return fig\n", "\n", "\n", "demo = gr.Blocks()\n", "\n", "with demo:\n", "    gr.Markdown(\n", "        r\"Let's do some kinematics! Choose the speed and angle to see the trajectory. Remember that the range $R = v_0^2 \\cdot \\frac{\\sin(2\\theta)}{g}$\"\n", "    )\n", "\n", "    with gr.Row():\n", "        speed = gr.Slider(1, 30, 25, label=\"Speed\")\n", "        angle = gr.Slider(0, 90, 45, label=\"Angle\")\n", "    output = gr.Plot()\n", "    btn = gr.Button(value=\"Run\")\n", "    btn.click(plot, [speed, angle], output)\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

demo/blocks_layout/run.ipynb

@@ -1 +1 @@
-{"cells": [{"cell_type": "markdown", "id": 302934307671667531413257853548643485645, "metadata": {}, "source": ["# Gradio Demo: blocks_layout"]}, {"cell_type": "code", "execution_count": null, "id": 272996653310673477252411125948039410165, "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": 288918539441861185822528903084949547379, "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/blocks_layout/config.json"]}, {"cell_type": "code", "execution_count": null, "id": 44380577570523278879349135829904343037, "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "\n", "\n", "demo = gr.Blocks()\n", "\n", "with demo:\n", "    with gr.Row():\n", "        gr.Image(interactive=True)\n", "        gr.Image()\n", "    with gr.Row():\n", "        gr.Textbox(label=\"Text\")\n", "        gr.Number(label=\"Count\")\n", "        gr.Radio(choices=[\"One\", \"Two\"])\n", "    with gr.Row():\n", "        with gr.Row():\n", "            with gr.Column():\n", "                gr.Textbox(label=\"Text\")\n", "                gr.Number(label=\"Count\")\n", "                gr.Radio(choices=[\"One\", \"Two\"])\n", "            gr.Image()\n", "            with gr.Column():\n", "                gr.Image(interactive=True)\n", "                gr.Image()\n", "    gr.Image()\n", "    gr.Textbox(label=\"Text\")\n", "    gr.Number(label=\"Count\")\n", "    gr.Radio(choices=[\"One\", \"Two\"])\n", "\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
+{"cells": [{"cell_type": "markdown", "id": 302934307671667531413257853548643485645, "metadata": {}, "source": ["# Gradio Demo: blocks_layout"]}, {"cell_type": "code", "execution_count": null, "id": 272996653310673477252411125948039410165, "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": 288918539441861185822528903084949547379, "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "\n", "\n", "demo = gr.Blocks()\n", "\n", "with demo:\n", "    with gr.Row():\n", "        gr.Image(interactive=True)\n", "        gr.Image()\n", "    with gr.Row():\n", "        gr.Textbox(label=\"Text\")\n", "        gr.Number(label=\"Count\")\n", "        gr.Radio(choices=[\"One\", \"Two\"])\n", "    with gr.Row():\n", "        with gr.Row():\n", "            with gr.Column():\n", "                gr.Textbox(label=\"Text\")\n", "                gr.Number(label=\"Count\")\n", "                gr.Radio(choices=[\"One\", \"Two\"])\n", "            gr.Image()\n", "            with gr.Column():\n", "                gr.Image(interactive=True)\n", "                gr.Image()\n", "    gr.Image()\n", "    gr.Textbox(label=\"Text\")\n", "    gr.Number(label=\"Count\")\n", "    gr.Radio(choices=[\"One\", \"Two\"])\n", "\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

demo/blocks_page_load/run.ipynb

@@ -1 +1 @@
-{"cells": [{"cell_type": "markdown", "id": 302934307671667531413257853548643485645, "metadata": {}, "source": ["# Gradio Demo: blocks_page_load"]}, {"cell_type": "code", "execution_count": null, "id": 272996653310673477252411125948039410165, "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": 288918539441861185822528903084949547379, "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/blocks_page_load/config.json"]}, {"cell_type": "code", "execution_count": null, "id": 44380577570523278879349135829904343037, "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "\n", "\n", "def print_message(n):\n", "    return \"Welcome! This page has loaded for \" + n\n", "\n", "\n", "with gr.Blocks() as demo:\n", "    t = gr.Textbox(\"Frank\", label=\"Name\")\n", "    t2 = gr.Textbox(label=\"Output\")\n", "    demo.load(print_message, t, t2)\n", "\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
+{"cells": [{"cell_type": "markdown", "id": 302934307671667531413257853548643485645, "metadata": {}, "source": ["# Gradio Demo: blocks_page_load"]}, {"cell_type": "code", "execution_count": null, "id": 272996653310673477252411125948039410165, "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": 288918539441861185822528903084949547379, "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "\n", "\n", "def print_message(n):\n", "    return \"Welcome! This page has loaded for \" + n\n", "\n", "\n", "with gr.Blocks() as demo:\n", "    t = gr.Textbox(\"Frank\", label=\"Name\")\n", "    t2 = gr.Textbox(label=\"Output\")\n", "    demo.load(print_message, t, t2)\n", "\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

demo/blocks_xray/run.ipynb

@@ -1 +1 @@
-{"cells": [{"cell_type": "markdown", "id": 302934307671667531413257853548643485645, "metadata": {}, "source": ["# Gradio Demo: blocks_xray"]}, {"cell_type": "code", "execution_count": null, "id": 272996653310673477252411125948039410165, "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": 288918539441861185822528903084949547379, "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/blocks_xray/config.json"]}, {"cell_type": "code", "execution_count": null, "id": 44380577570523278879349135829904343037, "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import random\n", "import time\n", "\n", "\n", "def xray_model(diseases, img):\n", "    time.sleep(4)\n", "    return [{disease: random.random() for disease in diseases}]\n", "\n", "\n", "def ct_model(diseases, img):\n", "    time.sleep(3)\n", "    return [{disease: 0.1 for disease in diseases}]\n", "\n", "with gr.Blocks() as demo:\n", "    gr.Markdown(\n", "        \"\"\"\n", "# Detect Disease From Scan\n", "With this model you can lorem ipsum\n", "- ipsum 1\n", "- ipsum 2\n", "\"\"\"\n", "    )\n", "    disease = gr.CheckboxGroup(\n", "        choices=[\"Covid\", \"Malaria\", \"Lung Cancer\"], label=\"Disease to Scan For\"\n", "    )\n", "\n", "    with gr.Tab(\"X-ray\") as x_tab:\n", "        with gr.Row():\n", "            xray_scan = gr.Image()\n", "            xray_results = gr.JSON()\n", "        xray_run = gr.Button(\"Run\")\n", "        xray_run.click(\n", "            xray_model,\n", "            inputs=[disease, xray_scan],\n", "            outputs=xray_results,\n", "            api_name=\"xray_model\"\n", "        )\n", "\n", "    with gr.Tab(\"CT Scan\"):\n", "        with gr.Row():\n", "            ct_scan = gr.Image()\n", "            ct_results = gr.JSON()\n", "        ct_run = gr.Button(\"Run\")\n", "        ct_run.click(\n", "            ct_model,\n", "            inputs=[disease, ct_scan],\n", "            outputs=ct_results,\n", "            api_name=\"ct_model\"\n", "        )\n", "\n", "    upload_btn = gr.Button(\"Upload Results\")\n", "    upload_btn.click(\n", "        lambda ct, xr: time.sleep(5),\n", "        inputs=[ct_results, xray_results],\n", "        outputs=[],\n", "    )\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
+{"cells": [{"cell_type": "markdown", "id": 302934307671667531413257853548643485645, "metadata": {}, "source": ["# Gradio Demo: blocks_xray"]}, {"cell_type": "code", "execution_count": null, "id": 272996653310673477252411125948039410165, "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": 288918539441861185822528903084949547379, "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import random\n", "import time\n", "\n", "\n", "def xray_model(diseases, img):\n", "    time.sleep(4)\n", "    return [{disease: random.random() for disease in diseases}]\n", "\n", "\n", "def ct_model(diseases, img):\n", "    time.sleep(3)\n", "    return [{disease: 0.1 for disease in diseases}]\n", "\n", "with gr.Blocks() as demo:\n", "    gr.Markdown(\n", "        \"\"\"\n", "# Detect Disease From Scan\n", "With this model you can lorem ipsum\n", "- ipsum 1\n", "- ipsum 2\n", "\"\"\"\n", "    )\n", "    disease = gr.CheckboxGroup(\n", "        choices=[\"Covid\", \"Malaria\", \"Lung Cancer\"], label=\"Disease to Scan For\"\n", "    )\n", "\n", "    with gr.Tab(\"X-ray\") as x_tab:\n", "        with gr.Row():\n", "            xray_scan = gr.Image()\n", "            xray_results = gr.JSON()\n", "        xray_run = gr.Button(\"Run\")\n", "        xray_run.click(\n", "            xray_model,\n", "            inputs=[disease, xray_scan],\n", "            outputs=xray_results,\n", "            api_name=\"xray_model\"\n", "        )\n", "\n", "    with gr.Tab(\"CT Scan\"):\n", "        with gr.Row():\n", "            ct_scan = gr.Image()\n", "            ct_results = gr.JSON()\n", "        ct_run = gr.Button(\"Run\")\n", "        ct_run.click(\n", "            ct_model,\n", "            inputs=[disease, ct_scan],\n", "            outputs=ct_results,\n", "            api_name=\"ct_model\"\n", "        )\n", "\n", "    upload_btn = gr.Button(\"Upload Results\")\n", "    upload_btn.click(\n", "        lambda ct, xr: time.sleep(5),\n", "        inputs=[ct_results, xray_results],\n", "        outputs=[],\n", "    )\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}