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requirements.txt

@@ -1,2 +1,2 @@
-gradio-client @ git+https://github.com/gradio-app/gradio@e75f2ca2da4f41f25459b98bedaa940c887e6a93#subdirectory=client/python
-https://gradio-builds.s3.amazonaws.com/e75f2ca2da4f41f25459b98bedaa940c887e6a93/gradio-4.38.1-py3-none-any.whl
+gradio-client @ git+https://github.com/gradio-app/gradio@7e8c829aad85d3d5a31a03f4f2e41483d1e6b53e#subdirectory=client/python
+https://gradio-builds.s3.amazonaws.com/7e8c829aad85d3d5a31a03f4f2e41483d1e6b53e/gradio-4.38.1-py3-none-any.whl

run.ipynb

@@ -1 +1 @@
-{"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", "def test_select_is_defined(n, evt: gr.SelectData):\n", "    assert isinstance(evt.index, list)\n", "    assert isinstance(evt.index[0], int)\n", "    return n + 1\n", "\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", "            num_select = gr.Number(label=\"# Select 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", "        output_img.select(test_select_is_defined, num_select, num_select)\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
+{"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", "def test_select_is_defined(n, evt: gr.SelectData):\n", "    assert isinstance(evt.index, list)\n", "    assert isinstance(evt.index[0], int)\n", "    return n + 1\n", "\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_input = gr.Number(label=\"# Input 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", "            num_select = gr.Number(label=\"# Select Events\", value=0)\n", "\n", "        input_img.upload(lambda s, n: (s, n + 1), [input_img, num_load], [output_img, num_load])\n", "        input_img.input(lambda n: n + 1, num_input, num_input)\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", "        output_img.select(test_select_is_defined, num_select, num_select)\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

run.py

@@ -14,11 +14,14 @@ with gr.Blocks() as demo:
             output_img = gr.Image(type="filepath", label="Output Image", sources=["upload", "clipboard"])
         with gr.Column():
             num_change = gr.Number(label="# Change Events", value=0)
+            num_input = gr.Number(label="# Input Events", value=0)
             num_load = gr.Number(label="# Upload Events", value=0)
             num_change_o = gr.Number(label="# Change Events Output", value=0)
             num_clear = gr.Number(label="# Clear Events", value=0)
             num_select = gr.Number(label="# Select Events", value=0)
+
         input_img.upload(lambda s, n: (s, n + 1), [input_img, num_load], [output_img, num_load])
+        input_img.input(lambda n: n + 1, num_input, num_input)
         input_img.change(lambda n: n + 1, num_change, num_change)
         input_img.clear(lambda n: n + 1, num_clear, num_clear)
         output_img.change(lambda n: n + 1, num_change_o, num_change_o)