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Update app.py
Browse files
app.py
CHANGED
@@ -11,6 +11,7 @@ client = None
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def initialize_client(api_key=None):
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global client
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api_key = os.getenv("TOGETHER_API_KEY")
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client = Together()
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def encode_image(image_path):
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@@ -32,7 +33,7 @@ def bot_streaming(image_path, history):
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prompt = """
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You are expert in computer vision and autos inspection from image analysis. Inspect the auto's radiator core support for damage resulting from a front-end
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collision. Check for any bent,
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and frame sections.
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Ensure that the radiator is securely mounted and assess if there are any signs of stress or deformation caused by the accident.
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then tell it as accidental if not then not accidental.
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@@ -82,61 +83,17 @@ def bot_streaming(image_path, history):
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history[-1] = ("Image uploaded", error_message)
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yield history
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#
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body_frame_data = [
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{"label": "Radiator Core Support"},
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{"label": "Right Strut Tower Apron"},
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{"label": "Left Strut Tower Apron"},
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{"label": "Right Front Rail"},
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{"label": "Left Front Rail"},
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{"label": "Cowl Panel Firewall"},
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{"label": "Right A Pillar"},
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{"label": "Left A Pillar"},
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{"label": "Right B Pillar"},
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{"label": "Left B Pillar"},
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{"label": "Right C Pillar"},
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{"label": "Left C Pillar"},
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{"label": "Boot Floor"},
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{"label": "Boot Lock Pillar"},
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{"label": "Rear Sub Frame"},
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{"label": "Front Sub Frame"},
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]
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# Define data for the Tyres
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tyre_data = [
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{"label": "Front Right Tyre"},
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{"label": "Front Left Tyre"},
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{"label": "Rear Right Tyre"},
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{"label": "Rear Left Tyre"},
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{"label": "Tyre Size"},
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{"label": "Rims"},
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{"label": "Wheel Caps"},
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]
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def create_category_section(data, name):
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with gr.Row():
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gr.Markdown(f"## {name}")
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for item in data:
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with gr.Column():
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gr.Markdown(f"### {item['label']}")
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image = gr.Image(type="filepath", label="Upload Image")
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chatbot = gr.Chatbot()
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image.upload(bot_streaming, inputs=[image, chatbot], outputs=chatbot)
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# Create the main interface
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with gr.Blocks() as demo:
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gr.Markdown("#
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gr.Markdown("Upload an image of
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# Display Tyres Section
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create_category_section(tyre_data, "Tyres")
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clear
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clear.click(lambda: None, None, None)
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if __name__ == "__main__":
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demo.launch(debug=True)
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def initialize_client(api_key=None):
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global client
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api_key = os.getenv("TOGETHER_API_KEY")
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print(api_key)
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client = Together()
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def encode_image(image_path):
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prompt = """
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You are expert in computer vision and autos inspection from image analysis. Inspect the auto's radiator core support for damage resulting from a front-end
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collision. Check for any bent, cracked, or misaligned components, including the core support bracket, mounting points,
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and frame sections.
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Ensure that the radiator is securely mounted and assess if there are any signs of stress or deformation caused by the accident.
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then tell it as accidental if not then not accidental.
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history[-1] = ("Image uploaded", error_message)
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yield history
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# Set up Gradio interface
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with gr.Blocks() as demo:
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gr.Markdown("# Radiator Accident Detection")
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gr.Markdown("Upload an image of a radiator to determine if it shows signs of an accident")
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chatbot = gr.Chatbot()
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img = gr.Image(type="filepath", label="Upload Radiator Image")
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clear = gr.Button("Clear")
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img.upload(bot_streaming, inputs=[img, chatbot], outputs=chatbot)
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clear.click(lambda: None, None, chatbot, queue=False)
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if __name__ == "__main__":
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demo.launch(debug=True)
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