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Update app.py
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app.py
CHANGED
@@ -103,7 +103,54 @@ def predict_answer(image, video, question):
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else:
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return "Unsupported file type. Please upload an image or video."
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def gradio_predict(image, video, question):
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@@ -147,5 +194,15 @@ with gr.Blocks(css = css) as app:
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btn.click(gradio_predict, inputs=[image, video, question], outputs=answer)
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app.launch(debug=True)
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else:
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return "Unsupported file type. Please upload an image or video."
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promt_cat_dog = """
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Annotate this image with this schema:
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{
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“description”: “Is there a cat in the image?”,
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“value”: “Cat”
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},
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{
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“description”: “Is there a dog in the image?”,
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“value”: “Dog”
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},
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{
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“description”: “Is there a horse in the image?”,
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“value”: “Horse”
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},
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provide me the answers as a dictionary with key as the string value of the variable value on top and its value should be 0 if it is Flase, else 1 if its is True
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"""
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promt_bus_people = """
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Annotate this image with this schema:
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{
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“description”: “Is there a bus in the image?”,
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“value”: “Bus”
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},
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{
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“description”: “Is there a bike in the image?”,
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“value”: “Bike”
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},
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provide me the answers as a dictionary with key as the string value of the variable value on top and its value should be 0 if it is Flase, else 1 if its is True
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"""
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promt_video = """
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Annotate this image with this schema:
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{
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“description”: “Is the person standing?”,
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“value”: “Standing”
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},
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{
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“description”: “Is the person hands free?”,
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“value”: “Hands-Free”
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}
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provide me the answers as a dictionary with key as the string value of the variable value on top and its value should be 0 if it is Flase, else 1 if its is True
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"""
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test_examples = [[None, "Images/cat_dog.jpeg", promt_cat_dog],
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[None,"Images/bus_people.jpeg", promt_bus_people],
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["videos/v1.mp4",None,promt_video],
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["videos/v2.mp4",None,promt_video],
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["videos/v3.mp4",None,promt_video]]
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def gradio_predict(image, video, question):
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btn.click(gradio_predict, inputs=[image, video, question], outputs=answer)
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# Define examples for images
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gr.Markdown("## Examples")
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gr.Examples(
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examples=test_examples,
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inputs=[image, video, question],
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outputs=[answer],
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fn=gradio_predict,
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cache_examples=True,
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)
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app.launch(debug=True)
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