debug: dff_nmf removed prob, boxes

yolov8.py

@@ -183,30 +183,30 @@ def dff_nmf(image, target_lyr, n_components):
     detections = results[0]  # The first element should contain the detection data
 
     # Access detection results
-    boxes = detections.boxes.xyxy.cpu().numpy()  # Bounding box coordinates (xyxy)
-    probs = detections.probs.cpu().numpy()      # Confidence scores (probabilities)
-    classes = detections.classes.cpu().numpy()  # Class IDs
+    #boxes = detections.boxes.xyxy.cpu().numpy()  # Bounding box coordinates (xyxy)
+    #probs = detections.probs.cpu().numpy()      # Confidence scores (probabilities)
+    #classes = detections.classes.cpu().numpy()  # Class IDs
 
     # Filter detections with confidence score > threshold (e.g., 0.5)
-    high_conf_indices = probs > 0.5
-    high_conf_boxes = boxes[high_conf_indices]
-    high_conf_classes = classes[high_conf_indices]
-    high_conf_probs = probs[high_conf_indices]
+    #high_conf_indices = probs > 0.5
+    #high_conf_boxes = boxes[high_conf_indices]
+    #high_conf_classes = classes[high_conf_indices]
+    #high_conf_probs = probs[high_conf_indices]
 
     # Example visualization and output processing
     fig, ax = plt.subplots(1, figsize=(8, 8))
     ax.axis("off")
     ax.imshow(rgb_img_float)
 
-    for box, cls, prob in zip(high_conf_boxes, high_conf_classes, high_conf_probs):
-        x1, y1, x2, y2 = box
-        rect = patches.Rectangle((x1, y1), x2 - x1, y2 - y1,
-                                 linewidth=2, edgecolor='r', facecolor='none')
-        ax.add_patch(rect)
-        ax.text(x1, y1, f"Class {cls}, Prob {prob:.2f}", color='r', fontsize=12, verticalalignment='top')
+    #for box, cls, prob in zip(high_conf_boxes, high_conf_classes, high_conf_probs):
+     #   x1, y1, x2, y2 = box
+      #  rect = patches.Rectangle((x1, y1), x2 - x1, y2 - y1,
+      #                           linewidth=2, edgecolor='r', facecolor='none')
+      #  ax.add_patch(rect)
+      #  ax.text(x1, y1, f"Class {cls}, Prob {prob:.2f}", color='r', fontsize=12, verticalalignment='top')
 
-    plt.subplots_adjust(left=0, right=1, top=1, bottom=0)
-    fig.canvas.draw()
+   # plt.subplots_adjust(left=0, right=1, top=1, bottom=0)
+    #fig.canvas.draw()
     image_array = np.array(fig.canvas.renderer.buffer_rgba())
     image_resized = cv2.resize(image_array, (640, 640))
     rgba_channels = cv2.split(image_resized)