Update app.py

app.py

@@ -1,13 +1,15 @@
+from flask import Flask, render_template, request
 import cv2
 import numpy as np
 from tensorflow.keras.models import load_model
 
+app = Flask(__name__)
+
 class ShelfClassifier:
     def __init__(self, model_path):
         self.model = load_model(model_path)
 
-    def classify_image(self, image_path):
-        image = cv2.imread(image_path)
+    def classify_image(self, image):
         image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
         resized_image = cv2.resize(image_rgb, (224, 224))
         resized_image = resized_image.astype('float32') / 255
@@ -17,12 +19,32 @@ class ShelfClassifier:
         class_label = "Disorganized or Empty" if class_index == 1 else "Organized"
         return class_label
 
-def main():
-    model_path = 'saved_model.h5'
-    classifier = ShelfClassifier(model_path)
-    image_path = 'your_image.jpg'  # Change to your image path
-    result = classifier.classify_image(image_path)
-    print("Classification Result:", result)
+@app.route('/', methods=['GET', 'POST'])
+def upload_image():
+    if request.method == 'POST':
+        # Check if the post request has the file part
+        if 'file' not in request.files:
+            return render_template('index.html', message='No file part')
+        file = request.files['file']
+        # If user does not select file, browser also
+        # submit an empty part without filename
+        if file.filename == '':
+            return render_template('index.html', message='No selected file')
+        if file:
+            # Read uploaded image
+            image = cv2.imdecode(np.fromstring(file.read(), np.uint8), cv2.IMREAD_COLOR)
+            # Initialize ShelfClassifier with the model
+            classifier = ShelfClassifier('saved_model.h5')
+            # Perform classification
+            class_label = classifier.classify_image(image)
+            # Draw bounding box if shelf is disorganized or empty
+            if class_label == "Disorganized or Empty":
+                # Draw red rectangle
+                cv2.rectangle(image, (0, 0), (image.shape[1], image.shape[0]), (255, 0, 0), 2)
+            # Save image with bounding box
+            cv2.imwrite('result.jpg', image)
+            return render_template('result.html', class_label=class_label)
+    return render_template('index.html')
 
-if __name__ == "__main__":
-    main()
+if __name__ == '__main__':
+    app.run(debug=True)