Yolo fixes with examples

README.md

@@ -340,11 +340,23 @@ Sample of annotated image along with its mask and settings is show below.
 }
 
 ```
-YOLO Format
+### YOLO Format 
+
+YOLO format is also supported by A.Lab. Below is an example of annotated ripe and unripe tomatoes. In this example, `0` represents ripe tomatoes and `1` represents unripe ones.
+
+![yolo_annotation_example](./sample_images/yolo_annotation_example.png)
+
+The label of the above image are as follows:
 ```
-Orange 0.0015012463401089847 0.0018903253731438908 0.0016967868433852144 0.0026982117835804955
+0 0.213673 0.474717 0.310212 0.498856
+0 0.554777 0.540507 0.306350 0.433638
+1 0.378432 0.681239 0.223970 0.268879
 ```
 
+Applying the generated labels we get following results.
+
+![yolo_with_generated_labels](./sample_images/yolo_applied_annotation.jpg)
+
 ## Troubleshooting [[documentation page]](https://annotate-docs.dwaste.live/troubleshooting)
 
 - Ensure that both the client and server are running.

server/app.py

@@ -564,47 +564,46 @@ def create_yolo_annotations(image_names, color_map=None):
 
                 # Convert points to normalized YOLO format
                 if points:
-                    xmin = min(point[0] for point in points) / width
-                    ymin = min(point[1] for point in points) / height
-                    xmax = max(point[0] for point in points) / width
-                    ymax = max(point[1] for point in points) / height
+                    xmin = min(point[0] for point in points)
+                    ymin = min(point[1] for point in points)
+                    xmax = max(point[0] for point in points)
+                    ymax = max(point[1] for point in points)
 
                     # YOLO format: class_index x_center y_center width height (all normalized)
-                    annotations.append(f"{class_name} {(xmin + xmax) / 2} {(ymin + ymax) / 2} {xmax - xmin} {ymax - ymin}")
+                    annotations.append(f"{class_name} {(xmin + xmax) / 2:.6f} {(ymin + ymax) / 2:.6f} {xmax - xmin:.6f} {ymax - ymin:.6f}")
 
         # Process box regions
         if boxRegions is not None:
             for index, region in boxRegions.iterrows():
                 class_name = region.get('class', 'unknown')
                 try:
-                    x = float(region['x'][1:-1]) * width if isinstance(region['x'], str) else float(region['x'][0]) * width
-                    y = float(region['y'][1:-1]) * height if isinstance(region['y'], str) else float(region['y'][0]) * height
-                    w = float(region['w'][1:-1]) * width if isinstance(region['w'], str) else float(region['w'][0]) * width
-                    h = float(region['h'][1:-1]) * height if isinstance(region['h'], str) else float(region['h'][0]) * height
+                    x = float(region['x'][1:-1]) if isinstance(region['x'], str) else float(region['x'][0])
+                    y = float(region['y'][1:-1]) if isinstance(region['y'], str) else float(region['y'][0])
+                    w = float(region['w'][1:-1]) if isinstance(region['w'], str) else float(region['w'][0])
+                    h = float(region['h'][1:-1]) if isinstance(region['h'], str) else float(region['h'][0])
                 except (ValueError, TypeError) as e:
                     raise ValueError(f"Invalid format in region dimensions: {region}, Error: {e}")
-
                 # YOLO format: class_index x_center y_center width height (all normalized)
-                annotations.append(f"{class_name} {x + w / 2} {y + h / 2} {w} {h}")
+                annotations.append(f"{class_name} {x + w / 2:.6f} {y + h / 2:.6f} {w:.6f} {h:.6f}")
 
         # Process circle/ellipse regions
         if circleRegions is not None:
             for index, region in circleRegions.iterrows():
                 class_name = region.get('class', 'unknown')
                 try:
-                    rx = float(region['rx'][1:-1]) * width if isinstance(region['rx'], str) else float(region['rx'][0]) * width
-                    ry = float(region['ry'][1:-1]) * height if isinstance(region['ry'], str) else float(region['ry'][0]) * height
-                    rw = float(region['rw'][1:-1]) * width if isinstance(region['rw'], str) else float(region['rw'][0]) * width
-                    rh = float(region['rh'][1:-1]) * height if isinstance(region['rh'], str) else float(region['rh'][0]) * height
+                    rx = float(region['rx'][1:-1]) * width if isinstance(region['rx'], str) else float(region['rx'][0])
+                    ry = float(region['ry'][1:-1]) * height if isinstance(region['ry'], str) else float(region['ry'][0])
+                    rw = float(region['rw'][1:-1]) * width if isinstance(region['rw'], str) else float(region['rw'][0])
+                    rh = float(region['rh'][1:-1]) * height if isinstance(region['rh'], str) else float(region['rh'][0])
                 except (ValueError, TypeError) as e:
                     raise ValueError(f"Invalid format in region dimensions: {region}, Error: {e}")
 
                 # For YOLO, if width and height are equal, it represents a circle
                 if rw == rh:
-                    annotations.append(f"{class_name} {rx} {ry} {rw} {rw}")  # Treat as circle
+                    annotations.append(f"{class_name} {rx:.6f} {ry:.6f} {rw:.6f} {rw:.6f}")  # Treat as circle
                 else:
                     # Treat as ellipse (YOLO does not directly support ellipse, so treat as box)
-                    annotations.append(f"{class_name} {rx + rw / 2} {ry + rh / 2} {rw} {rh}")
+                    annotations.append(f"{class_name} {rx + rw / 2:.6f} {ry + rh / 2:.6f} {rw:.6f} {rh:.6f}")
 
         # Append annotations for current image to all_annotations list
         all_annotations.extend(annotations)

server/examples/check_label.py

@@ -0,0 +1,51 @@
+import cv2
+import os
+
+# Function to draw bounding boxes
+def draw_bboxes(image_path, label_path, output_path):
+    # Define colors for different classes
+    colors = [(0, 0, 255), (0, 255, 0)]  # Example colors for two classes: green and red for unripe and riped
+
+    # Read the image
+    image = cv2.imread(image_path)
+    height, width, _ = image.shape
+
+    # Read the label file
+    with open(label_path, 'r') as f:
+        labels = f.readlines()
+
+    for label in labels:
+        label_data = label.strip().split()
+        class_id = int(label_data[0])
+        x_center, y_center, bbox_width, bbox_height = map(float, label_data[1:])
+
+        # Convert normalized coordinates to pixel coordinates
+        x_center *= width
+        y_center *= height
+        bbox_width *= width
+        bbox_height *= height
+
+        # Calculate top-left and bottom-right coordinates
+        x1 = int(x_center - bbox_width / 2)
+        y1 = int(y_center - bbox_height / 2)
+        x2 = int(x_center + bbox_width / 2)
+        y2 = int(y_center + bbox_height / 2)
+
+        # Draw the bounding box with a color based on class ID
+        color = colors[class_id]
+        cv2.rectangle(image, (x1, y1), (x2, y2), color, 2)
+        cv2.putText(image, str(class_id), (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 2)
+
+    # Save the output image
+    cv2.imwrite(output_path, image)
+
+
+# Paths to the image, label, and output
+image_path = './tomato_example.jpeg'
+label_path = './tomato_example.txt'
+output_path = './output_tomato_example.jpg'
+
+# Draw bounding boxes on the image
+draw_bboxes(image_path, label_path, output_path)
+
+print(f"Output image saved to {output_path}")

server/examples/tomato_example.txt

@@ -0,0 +1,3 @@
+0 0.213673 0.474717 0.310212 0.498856
+0 0.554777 0.540507 0.306350 0.433638
+1 0.378432 0.681239 0.223970 0.268879

server/requirements.txt

@@ -1,4 +1,4 @@
-flask
+opencv-python
 flask-cors
 pandas
 pillow