Fix ambiguous variable names (#13864)

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: Alex Pasquali <alexpasquali98@gmail.com>

ultralytics/data/converter.py

@@ -329,8 +329,7 @@ def convert_coco(
 
         if lvis:
             with open((Path(save_dir) / json_file.name.replace("lvis_v1_", "").replace(".json", ".txt")), "a") as f:
-                for l in image_txt:
-                    f.write(f"{l}\n")
+                f.writelines(f"{line}\n" for line in image_txt)
 
     LOGGER.info(f"{'LVIS' if lvis else 'COCO'} data converted successfully.\nResults saved to {save_dir.resolve()}")
 
@@ -534,25 +533,25 @@ def yolo_bbox2segment(im_dir, save_dir=None, sam_model="sam_b.pt"):
 
     LOGGER.info("Detection labels detected, generating segment labels by SAM model!")
     sam_model = SAM(sam_model)
-    for l in tqdm(dataset.labels, total=len(dataset.labels), desc="Generating segment labels"):
-        h, w = l["shape"]
-        boxes = l["bboxes"]
+    for label in tqdm(dataset.labels, total=len(dataset.labels), desc="Generating segment labels"):
+        h, w = label["shape"]
+        boxes = label["bboxes"]
         if len(boxes) == 0:  # skip empty labels
             continue
         boxes[:, [0, 2]] *= w
         boxes[:, [1, 3]] *= h
-        im = cv2.imread(l["im_file"])
+        im = cv2.imread(label["im_file"])
         sam_results = sam_model(im, bboxes=xywh2xyxy(boxes), verbose=False, save=False)
-        l["segments"] = sam_results[0].masks.xyn
+        label["segments"] = sam_results[0].masks.xyn
 
     save_dir = Path(save_dir) if save_dir else Path(im_dir).parent / "labels-segment"
     save_dir.mkdir(parents=True, exist_ok=True)
-    for l in dataset.labels:
+    for label in dataset.labels:
         texts = []
-        lb_name = Path(l["im_file"]).with_suffix(".txt").name
+        lb_name = Path(label["im_file"]).with_suffix(".txt").name
         txt_file = save_dir / lb_name
-        cls = l["cls"]
-        for i, s in enumerate(l["segments"]):
+        cls = label["cls"]
+        for i, s in enumerate(label["segments"]):
             line = (int(cls[i]), *s.reshape(-1))
             texts.append(("%g " * len(line)).rstrip() % line)
         if texts:

ultralytics/data/split_dota.py

@@ -26,8 +26,8 @@ def bbox_iof(polygon1, bbox2, eps=1e-6):
         bbox2 (np.ndarray): Bounding boxes, (n ,4).
     """
     polygon1 = polygon1.reshape(-1, 4, 2)
-    lt_point = np.min(polygon1, axis=-2)
-    rb_point = np.max(polygon1, axis=-2)
+    lt_point = np.min(polygon1, axis=-2)  # left-top
+    rb_point = np.max(polygon1, axis=-2)  # right-bottom
     bbox1 = np.concatenate([lt_point, rb_point], axis=-1)
 
     lt = np.maximum(bbox1[:, None, :2], bbox2[..., :2])
@@ -35,8 +35,8 @@ def bbox_iof(polygon1, bbox2, eps=1e-6):
     wh = np.clip(rb - lt, 0, np.inf)
     h_overlaps = wh[..., 0] * wh[..., 1]
 
-    l, t, r, b = (bbox2[..., i] for i in range(4))
-    polygon2 = np.stack([l, t, r, t, r, b, l, b], axis=-1).reshape(-1, 4, 2)
+    left, top, right, bottom = (bbox2[..., i] for i in range(4))
+    polygon2 = np.stack([left, top, right, top, right, bottom, left, bottom], axis=-1).reshape(-1, 4, 2)
 
     sg_polys1 = [Polygon(p) for p in polygon1]
     sg_polys2 = [Polygon(p) for p in polygon2]

ultralytics/engine/model.py

@@ -142,7 +142,6 @@ class Model(nn.Module):
         # Check if Triton Server model
         elif self.is_triton_model(model):
             self.model_name = self.model = model
-            self.task = task
             return
 
         # Load or create new YOLO model

ultralytics/models/sam/modules/tiny_encoder.py

@@ -384,8 +384,8 @@ class TinyViTBlock(nn.Module):
         convolution.
         """
         h, w = self.input_resolution
-        b, l, c = x.shape
-        assert l == h * w, "input feature has wrong size"
+        b, hw, c = x.shape  # batch, height*width, channels
+        assert hw == h * w, "input feature has wrong size"
         res_x = x
         if h == self.window_size and w == self.window_size:
             x = self.attn(x)
@@ -394,13 +394,13 @@ class TinyViTBlock(nn.Module):
             pad_b = (self.window_size - h % self.window_size) % self.window_size
             pad_r = (self.window_size - w % self.window_size) % self.window_size
             padding = pad_b > 0 or pad_r > 0
-
             if padding:
                 x = F.pad(x, (0, 0, 0, pad_r, 0, pad_b))
 
             pH, pW = h + pad_b, w + pad_r
             nH = pH // self.window_size
             nW = pW // self.window_size
+
             # Window partition
             x = (
                 x.view(b, nH, self.window_size, nW, self.window_size, c)
@@ -408,19 +408,18 @@ class TinyViTBlock(nn.Module):
                 .reshape(b * nH * nW, self.window_size * self.window_size, c)
             )
             x = self.attn(x)
+
             # Window reverse
             x = x.view(b, nH, nW, self.window_size, self.window_size, c).transpose(2, 3).reshape(b, pH, pW, c)
-
             if padding:
                 x = x[:, :h, :w].contiguous()
 
-            x = x.view(b, l, c)
+            x = x.view(b, hw, c)
 
         x = res_x + self.drop_path(x)
-
         x = x.transpose(1, 2).reshape(b, c, h, w)
         x = self.local_conv(x)
-        x = x.view(b, c, l).transpose(1, 2)
+        x = x.view(b, c, hw).transpose(1, 2)
 
         return x + self.drop_path(self.mlp(x))
 

ultralytics/nn/modules/__init__.py

@@ -133,6 +133,7 @@ __all__ = (
     "ResNetLayer",
     "OBB",
     "WorldDetect",
+    "v10Detect",
     "ImagePoolingAttn",
     "ContrastiveHead",
     "BNContrastiveHead",

ultralytics/nn/modules/block.py

@@ -40,7 +40,6 @@ __all__ = (
     "SPPELAN",
     "CBFuse",
     "CBLinear",
-    "Silence",
     "RepVGGDW",
     "CIB",
     "C2fCIB",

ultralytics/solutions/__init__.py

@@ -15,6 +15,7 @@ __all__ = (
     "Heatmap",
     "ObjectCounter",
     "ParkingManagement",
+    "ParkingPtsSelection",
     "QueueManager",
     "SpeedEstimator",
     "Analytics",