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Update app.py
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app.py
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import gradio as gr
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ai_optimizer = gr.Interface.load("models/facebook/dino-vitb16")
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# Define the Gradio interface
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iface = gr.Interface(
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fn=
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inputs=
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outputs=[
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gr.outputs.Textbox(label="Optimizations"),
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gr.outputs.Textbox(label="Cost Estimate"),
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iface.launch()
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import gradio as gr
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from gradio.inputs import File
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from gradio.outputs import Text, Image
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import os
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import torch
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from PIL import Image as PilImage
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from torchvision.transforms import ToTensor
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# Load the DINO model
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ai_optimizer = gr.Interface.load("models/facebook/dino-vitb16")
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def load_data(image_file):
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"""
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This function should load the data from the provided image file.
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This will convert the image file into a PIL Image.
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"""
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image = PilImage.open(image_file)
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return image
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def load_model():
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"""
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This function should load your model. Here, we're returning the DINO model.
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"""
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model = ai_optimizer
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return model
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def generate_text_report(analysis):
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"""
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This function should generate a text report based on the analysis made by your model.
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Here, we're simply returning a placeholder.
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"""
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text_report = "your text report"
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return text_report
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def generate_updated_blueprint_image(analysis):
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"""
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This function should generate an image based on the analysis made by your model.
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Here, we're simply returning a placeholder.
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"""
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image = "your image"
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return image
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def analyze_blueprint(image_file):
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image = load_data(image_file)
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model = load_model()
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# Transform the image to tensor
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transform = ToTensor()
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image_tensor = transform(image)
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# Add an extra dimension at the start for the batch size
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image_tensor = image_tensor.unsqueeze(0)
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# Pass the image through the model
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analysis = model.predict(image_tensor)
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text_report = generate_text_report(analysis)
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updated_blueprint = generate_updated_blueprint_image(analysis)
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return text_report, updated_blueprint
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iface = gr.Interface(
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fn=analyze_blueprint,
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inputs=File(label="Input Blueprint Image"),
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outputs=[Text(label="Analysis and Cost Estimation"), Image(plot=True, label="Updated Blueprint")],
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title="Blueprint Analyzer",
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description="Upload a blueprint image and get back an analysis and cost estimation."
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)
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if __name__ == "__main__":
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iface.launch()
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