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Update app.py
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app.py
CHANGED
@@ -22,20 +22,19 @@ st.title("Table Detection in Images")
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uploaded_file = st.file_uploader("Upload an image", type=["png", "jpg", "jpeg"])
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# Process Image and Display Results
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if uploaded_file:
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image = Image.open(uploaded_file).convert("RGB")
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inputs = image_processor(images=image, return_tensors="pt")
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outputs = model(**inputs)
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target_sizes = torch.tensor([image.size[::-1]])
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results = image_processor.post_process_object_detection(outputs, threshold=0.9, target_sizes=target_sizes)[0]
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st.image(image) # Display the uploaded image
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for score, label, box in zip(results["scores"], results["labels"], results["boxes"]):
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box = [round(i, 2) for i in box.tolist()]
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st.write(
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f"Detected {model.config.id2label[label.item()]} with confidence "
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f"{round(score.item(), 3)} at location {box}"
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)
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uploaded_file = st.file_uploader("Upload an image", type=["png", "jpg", "jpeg"])
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# Process Image and Display Results
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if uploaded_file:
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image = Image.open(uploaded_file).convert("RGB")
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inputs = image_processor(images=image, return_tensors="pt")
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outputs = model(**inputs)
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target_sizes = torch.tensor([image.size[::-1]])
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results = image_processor.post_process_object_detection(outputs, threshold=0.9, target_sizes=target_sizes)[0]
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st.image(image) # Display the uploaded image
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for score, label, box in zip(results["scores"], results["labels"], results["boxes"]):
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box = [round(i, 2) for i in box.tolist()]
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st.write(
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f"Detected {model.config.id2label[label.item()]} with confidence "
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f"{round(score.item(), 3)} at location {box}"
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)
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