Create app.py

app.py

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+import cv2
+import numpy as np
+from PIL import Image
+import gradio as gr
+from pdf2image import convert_from_path  # Import the PDF-to-image conversion library
+
+# Function to calculate materials based on blueprint dimensions
+def calculate_materials_from_dimensions(wall_area, foundation_area):
+    materials = {
+        "cement": 0,
+        "bricks": 0,
+        "steel": 0
+    }
+
+    # Wall calculations (in m²)
+    if wall_area > 0:
+        materials['cement'] += wall_area * 10  # 10 kg cement per m² for walls
+        materials['bricks'] += wall_area * 500  # 500 bricks per m² for walls
+        materials['steel'] += wall_area * 2  # 2 kg steel per m² for walls
+
+    # Foundation calculations (in m²)
+    if foundation_area > 0:
+        materials['cement'] += foundation_area * 20  # 20 kg cement per m² for foundation
+        materials['bricks'] += foundation_area * 750  # 750 bricks per m² for foundation
+        materials['steel'] += foundation_area * 5  # 5 kg steel per m² for foundation
+
+    return materials
+
+# Function to process the blueprint and extract dimensions
+def process_blueprint(image_path):
+    image = None
+    try:
+        # Check if the uploaded file is a PDF
+        if image_path.lower().endswith(".pdf"):
+            try:
+                # Convert the PDF to an image (first page)
+                images = convert_from_path(image_path, first_page=1, last_page=1)
+                image = np.array(images[0])  # Get the first page
+                print("Successfully converted PDF to image.")
+            except Exception as e:
+                print(f"Error processing the PDF file: {e}")
+                raise ValueError("Error processing the PDF file. Please ensure the file is a valid blueprint PDF.")
+        else:
+            # Open the image file
+            image = cv2.imread(image_path)
+            print("Successfully loaded image.")
+
+    except Exception as e:
+        print(f"Error loading file: {e}")
+        raise ValueError("Error loading the image. Please try again with a valid image or PDF file.")
+    
+    # Check if image is successfully loaded
+    if image is None:
+        raise ValueError("Could not load the image or PDF file.")
+    
+    # Convert to grayscale for easier processing
+    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+
+    # Apply edge detection to find lines (walls)
+    edges = cv2.Canny(gray, 50, 150, apertureSize=3)
+
+    # Use Hough Transform to detect lines (walls)
+    lines = cv2.HoughLinesP(edges, 1, np.pi / 180, threshold=100, minLineLength=50, maxLineGap=10)
+
+    # Calculate total wall length (in pixels)
+    total_wall_length_pixels = 0
+    if lines is not None:
+        for line in lines:
+            x1, y1, x2, y2 = line[0]
+            length = np.sqrt((x2 - x1) ** 2 + (y2 - y1) ** 2)
+            total_wall_length_pixels += length
+
+    # From the blueprint, we know the dimensions (27 m × 9.78 m)
+    image_height, image_width = image.shape[:2]
+    blueprint_width_m = 27  # From the blueprint (27 m)
+    blueprint_height_m = 9.78  # From the blueprint (9.78 m)
+
+    # Calculate pixel-to-meter ratio
+    pixel_to_meter_width = blueprint_width_m / image_width
+    pixel_to_meter_height = blueprint_height_m / image_height
+    pixel_to_meter = (pixel_to_meter_width + pixel_to_meter_height) / 2  # Average for simplicity
+
+    # Convert wall length to meters
+    total_wall_length_m = total_wall_length_pixels * pixel_to_meter
+
+    # Estimate wall area (assume wall height of 3 m for simplicity)
+    wall_height_m = 3  # Standard room height
+    wall_area = total_wall_length_m * wall_height_m
+
+    # Estimate foundation area (based on the blueprint's total area)
+    total_area = blueprint_width_m * blueprint_height_m  # 27 m × 9.78 m
+    foundation_area = total_area * 0.1  # Assume 10% of the total area is foundation
+
+    # Calculate materials
+    materials = calculate_materials_from_dimensions(wall_area, foundation_area)
+
+    # Format the output
+    formatted_materials = {
+        "cement": f"{materials['cement']:.2f} kg",
+        "bricks": f"{materials['bricks']:.0f} units",
+        "steel": f"{materials['steel']:.2f} kg"
+    }
+
+    return formatted_materials
+
+# Set up Gradio interface
+interface = gr.Interface(
+    fn=process_blueprint,
+    inputs=gr.File(label="Upload Blueprint (Image or PDF)", type="filepath"),  # Support both image and PDF files
+    outputs=gr.JSON(label="Material Estimates"),
+    title="Blueprint Material Estimator",
+    description="Upload a blueprint image or PDF to estimate construction materials."
+)
+
+# Launch the interface
+if __name__ == "__main__":
+    interface.launch(share=False)