Update app.py

app.py

@@ -65,25 +65,25 @@ def preprocess_image(image):
     # Convert to numpy array
     img_array = np.array(image)
     
-    # Convert to RGB if needed
-    if len(img_array.shape) == 2:  # Grayscale
-        img_array = cv2.cvtColor(img_array, cv2.COLOR_GRAY2RGB)
-    elif img_array.shape[2] == 4:  # RGBA
-        img_array = cv2.cvtColor(img_array, cv2.COLOR_RGBA2RGB)
+    # # Convert to RGB if needed
+    # if len(img_array.shape) == 2:  # Grayscale
+    #     img_array = cv2.cvtColor(img_array, cv2.COLOR_GRAY2RGB)
+    # elif img_array.shape[2] == 4:  # RGBA
+    #     img_array = cv2.cvtColor(img_array, cv2.COLOR_RGBA2RGB)
     
-    # Preprocess image similar to training
-    img_hsv = cv2.cvtColor(img_array, cv2.COLOR_RGB2HSV)
-    img_hsv[:, :, 2] = cv2.equalizeHist(img_hsv[:, :, 2])
-    img_array = cv2.cvtColor(img_hsv, cv2.COLOR_HSV2RGB)
+    # # Preprocess image similar to training
+    # img_hsv = cv2.cvtColor(img_array, cv2.COLOR_RGB2HSV)
+    # img_hsv[:, :, 2] = cv2.equalizeHist(img_hsv[:, :, 2])
+    # img_array = cv2.cvtColor(img_hsv, cv2.COLOR_HSV2RGB)
     
-    # Adjust brightness
-    target_brightness = 150
-    current_brightness = np.mean(img_array)
-    alpha = target_brightness / (current_brightness + 1e-5)
-    img_array = cv2.convertScaleAbs(img_array, alpha=alpha, beta=0)
+    # # Adjust brightness
+    # target_brightness = 150
+    # current_brightness = np.mean(img_array)
+    # alpha = target_brightness / (current_brightness + 1e-5)
+    # img_array = cv2.convertScaleAbs(img_array, alpha=alpha, beta=0)
     
-    # Apply Gaussian blur
-    img_array = cv2.GaussianBlur(img_array, (5, 5), 0)
+    # # Apply Gaussian blur
+    # img_array = cv2.GaussianBlur(img_array, (5, 5), 0)
     
     # Resize
     img_array = cv2.resize(img_array, (256, 256))