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Browse files- requirements.txt +1 -1
- run.ipynb +1 -1
- run.py +8 -0
requirements.txt
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https://gradio-builds.s3.amazonaws.com/
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https://gradio-builds.s3.amazonaws.com/b1b78c2168e24fb65251a9b9b6cbc9382179a8ca/gradio-4.12.0-py3-none-any.whl
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run.ipynb
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{"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}
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{"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}
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run.py
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import gradio as gr
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with gr.Blocks() as demo:
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with gr.Row():
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with gr.Column():
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num_load = gr.Number(label="# Upload Events", value=0)
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num_change_o = gr.Number(label="# Change Events Output", value=0)
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num_clear = gr.Number(label="# Clear Events", value=0)
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input_img.upload(lambda s, n: (s, n + 1), [input_img, num_load], [output_img, num_load])
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input_img.change(lambda n: n + 1, num_change, num_change)
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input_img.clear(lambda n: n + 1, num_clear, num_clear)
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output_img.change(lambda n: n + 1, num_change_o, num_change_o)
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if __name__ == "__main__":
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demo.launch()
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import gradio as gr
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def test_select_is_defined(n, evt: gr.SelectData):
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assert isinstance(evt.index, list)
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assert isinstance(evt.index[0], int)
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return n + 1
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with gr.Blocks() as demo:
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with gr.Row():
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with gr.Column():
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num_load = gr.Number(label="# Upload Events", value=0)
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num_change_o = gr.Number(label="# Change Events Output", value=0)
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num_clear = gr.Number(label="# Clear Events", value=0)
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num_select = gr.Number(label="# Select Events", value=0)
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input_img.upload(lambda s, n: (s, n + 1), [input_img, num_load], [output_img, num_load])
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input_img.change(lambda n: n + 1, num_change, num_change)
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input_img.clear(lambda n: n + 1, num_clear, num_clear)
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output_img.change(lambda n: n + 1, num_change_o, num_change_o)
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output_img.select(test_select_is_defined, num_select, num_select)
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if __name__ == "__main__":
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demo.launch()
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