run.ipynb

{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: image_component_events"]}, {"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", "with gr.Blocks() as demo:\n", "    with gr.Row():\n", "        with gr.Column():\n", "            input_img = gr.Image(type=\"filepath\", label=\"Input Image\", sources=[\"upload\", \"clipboard\"])\n", "        with gr.Column():\n", "            output_img = gr.Image(type=\"filepath\", label=\"Output Image\", sources=[\"upload\", \"clipboard\"])\n", "        with gr.Column():\n", "            num_change = gr.Number(label=\"# Change Events\", value=0)\n", "            num_load = gr.Number(label=\"# Upload Events\", value=0)\n", "            num_change_o = gr.Number(label=\"# Change Events Output\", value=0)\n", "            num_clear = gr.Number(label=\"# Clear Events\", value=0)\n", "        input_img.upload(lambda s, n: (s, n + 1), [input_img, num_load], [output_img, num_load])\n", "        input_img.change(lambda n: n + 1, num_change, num_change)\n", "        input_img.clear(lambda n: n + 1, num_clear, num_clear)\n", "        output_img.change(lambda n: n + 1, num_change_o, num_change_o)\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}