`ultralytics 8.0.56` PyTorch 2.0 support and minor fixes (#1538)

Co-authored-by: N-Friederich <127681326+N-Friederich@users.noreply.github.com>
Co-authored-by: Uhrendoktor <36703334+Uhrendoktor@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Laughing <61612323+Laughing-q@users.noreply.github.com>
Co-authored-by: Aman Agarwal <amanag.11@gmail.com>
Co-authored-by: ExtReMLapin <3909752+ExtReMLapin@users.noreply.github.com>
Co-authored-by: Nadav Eidelstein <30617226+nodeav@users.noreply.github.com>

.github/workflows/ci.yaml

@@ -7,7 +7,7 @@ on:
   push:
     branches: [main]
   pull_request:
-    branches: [main]
+    branches: [main, updates]
   schedule:
     - cron: '0 0 * * *'  # runs at 00:00 UTC every day
 
@@ -105,7 +105,9 @@ jobs:
           from ultralytics.yolo.utils.benchmarks import benchmark
           benchmark(model='${{ matrix.model }}-cls.pt', imgsz=160, half=False, hard_fail=0.61)
       - name: Benchmark Summary
-        run: cat benchmarks.log
+        run: |
+          cat benchmarks.log
+          echo "$(cat benchmarks.log)" >> $GITHUB_STEP_SUMMARY
 
   Tests:
     timeout-minutes: 60
@@ -133,9 +135,9 @@ jobs:
         run: |
           python -m pip install --upgrade pip wheel
           if [ "${{ matrix.torch }}" == "1.8.0" ]; then
-              pip install -e '.[export]' torch==1.8.0 torchvision==0.9.0 pytest --extra-index-url https://download.pytorch.org/whl/cpu
+              pip install -e . torch==1.8.0 torchvision==0.9.0 pytest --extra-index-url https://download.pytorch.org/whl/cpu
           else
-              pip install -e '.[export]' pytest --extra-index-url https://download.pytorch.org/whl/cpu
+              pip install -e . pytest --extra-index-url https://download.pytorch.org/whl/cpu
           fi
       - name: Check environment
         run: |

README.md

@@ -32,20 +32,17 @@ To request an Enterprise License please complete the form at [Ultralytics Licens
   <a href="https://github.com/ultralytics" style="text-decoration:none;">
     <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-github.png" width="2%" alt="" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
-    <a href="https://www.linkedin.com/company/ultralytics/" style="text-decoration:none;">
+  <a href="https://www.linkedin.com/company/ultralytics" style="text-decoration:none;">
     <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-linkedin.png" width="2%" alt="" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
   <a href="https://twitter.com/ultralytics" style="text-decoration:none;">
     <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-twitter.png" width="2%" alt="" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
-    <a href="https://www.producthunt.com/@glenn_jocher" style="text-decoration:none;">
-      <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-producthunt.png" width="2%" alt="" /></a>
-    <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
   <a href="https://youtube.com/ultralytics" style="text-decoration:none;">
     <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-youtube.png" width="2%" alt="" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
-    <a href="https://www.facebook.com/ultralytics" style="text-decoration:none;">
+  <a href="https://www.tiktok.com/@ultralytics" style="text-decoration:none;">
-      <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-facebook.png" width="2%" alt="" /></a>
+    <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-tiktok.png" width="2%" alt="" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
   <a href="https://www.instagram.com/ultralytics/" style="text-decoration:none;">
     <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-instagram.png" width="2%" alt="" /></a>
@@ -262,20 +259,17 @@ the [Ultralytics Community Forum](https://community.ultralytics.com/).
   <a href="https://github.com/ultralytics" style="text-decoration:none;">
     <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-github.png" width="3%" alt="" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="3%" alt="" />
-  <a href="https://www.linkedin.com/company/ultralytics/" style="text-decoration:none;">
+  <a href="https://www.linkedin.com/company/ultralytics" style="text-decoration:none;">
     <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-linkedin.png" width="3%" alt="" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="3%" alt="" />
   <a href="https://twitter.com/ultralytics" style="text-decoration:none;">
     <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-twitter.png" width="3%" alt="" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="3%" alt="" />
-  <a href="https://www.producthunt.com/@glenn_jocher" style="text-decoration:none;">
-    <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-producthunt.png" width="3%" alt="" /></a>
-  <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="3%" alt="" />
   <a href="https://youtube.com/ultralytics" style="text-decoration:none;">
     <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-youtube.png" width="3%" alt="" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="3%" alt="" />
-  <a href="https://www.facebook.com/ultralytics" style="text-decoration:none;">
+  <a href="https://www.tiktok.com/@ultralytics" style="text-decoration:none;">
-    <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-facebook.png" width="3%" alt="" /></a>
+    <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-tiktok.png" width="3%" alt="" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="3%" alt="" />
   <a href="https://www.instagram.com/ultralytics/" style="text-decoration:none;">
     <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-instagram.png" width="3%" alt="" /></a>

README.zh-CN.md

@@ -28,20 +28,17 @@ SOTA 模型。它在以前成功的 YOLO 版本基础上，引入了新的功能
   <a href="https://github.com/ultralytics" style="text-decoration:none;">
     <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-github.png" width="2%" alt="" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
-    <a href="https://www.linkedin.com/company/ultralytics/" style="text-decoration:none;">
+  <a href="https://www.linkedin.com/company/ultralytics" style="text-decoration:none;">
     <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-linkedin.png" width="2%" alt="" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
   <a href="https://twitter.com/ultralytics" style="text-decoration:none;">
     <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-twitter.png" width="2%" alt="" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
-    <a href="https://www.producthunt.com/@glenn_jocher" style="text-decoration:none;">
-      <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-producthunt.png" width="2%" alt="" /></a>
-    <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
   <a href="https://youtube.com/ultralytics" style="text-decoration:none;">
     <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-youtube.png" width="2%" alt="" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
-    <a href="https://www.facebook.com/ultralytics" style="text-decoration:none;">
+  <a href="https://www.tiktok.com/@ultralytics" style="text-decoration:none;">
-      <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-facebook.png" width="2%" alt="" /></a>
+    <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-tiktok.png" width="2%" alt="" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
   <a href="https://www.instagram.com/ultralytics/" style="text-decoration:none;">
     <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-instagram.png" width="2%" alt="" /></a>
@@ -239,20 +236,17 @@ YOLOv8 在两种不同的 License 下可用：
   <a href="https://github.com/ultralytics" style="text-decoration:none;">
     <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-github.png" width="3%" alt="" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="3%" alt="" />
-  <a href="https://www.linkedin.com/company/ultralytics/" style="text-decoration:none;">
+  <a href="https://www.linkedin.com/company/ultralytics" style="text-decoration:none;">
     <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-linkedin.png" width="3%" alt="" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="3%" alt="" />
   <a href="https://twitter.com/ultralytics" style="text-decoration:none;">
     <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-twitter.png" width="3%" alt="" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="3%" alt="" />
-  <a href="https://www.producthunt.com/@glenn_jocher" style="text-decoration:none;">
-    <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-producthunt.png" width="3%" alt="" /></a>
-  <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="3%" alt="" />
   <a href="https://youtube.com/ultralytics" style="text-decoration:none;">
     <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-youtube.png" width="3%" alt="" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="3%" alt="" />
-  <a href="https://www.facebook.com/ultralytics" style="text-decoration:none;">
+  <a href="https://www.tiktok.com/@ultralytics" style="text-decoration:none;">
-    <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-facebook.png" width="3%" alt="" /></a>
+    <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-tiktok.png" width="3%" alt="" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="3%" alt="" />
   <a href="https://www.instagram.com/ultralytics/" style="text-decoration:none;">
     <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-instagram.png" width="3%" alt="" /></a>

docs/app.md

@@ -7,20 +7,17 @@
   <a href="https://github.com/ultralytics" style="text-decoration:none;">
     <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-github.png" width="2%" alt="" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
-  <a href="https://www.linkedin.com/company/ultralytics/" style="text-decoration:none;">
+  <a href="https://www.linkedin.com/company/ultralytics" style="text-decoration:none;">
     <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-linkedin.png" width="2%" alt="" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
   <a href="https://twitter.com/ultralytics" style="text-decoration:none;">
     <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-twitter.png" width="2%" alt="" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
-  <a href="https://www.producthunt.com/@glenn_jocher" style="text-decoration:none;">
-    <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-producthunt.png" width="2%" alt="" /></a>
-  <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
   <a href="https://youtube.com/ultralytics" style="text-decoration:none;">
     <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-youtube.png" width="2%" alt="" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
-  <a href="https://www.facebook.com/ultralytics" style="text-decoration:none;">
+  <a href="https://www.tiktok.com/@ultralytics" style="text-decoration:none;">
-    <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-facebook.png" width="2%" alt="" /></a>
+    <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-tiktok.png" width="2%" alt="" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
   <a href="https://www.instagram.com/ultralytics/" style="text-decoration:none;">
     <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-instagram.png" width="2%" alt="" /></a>

docs/hub.md

@@ -7,20 +7,17 @@
   <a href="https://github.com/ultralytics" style="text-decoration:none;">
     <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-github.png" width="2%" alt="" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
-  <a href="https://www.linkedin.com/company/ultralytics/" style="text-decoration:none;">
+  <a href="https://www.linkedin.com/company/ultralytics" style="text-decoration:none;">
     <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-linkedin.png" width="2%" alt="" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
   <a href="https://twitter.com/ultralytics" style="text-decoration:none;">
     <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-twitter.png" width="2%" alt="" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
-  <a href="https://www.producthunt.com/@glenn_jocher" style="text-decoration:none;">
-    <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-producthunt.png" width="2%" alt="" /></a>
-  <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
   <a href="https://youtube.com/ultralytics" style="text-decoration:none;">
     <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-youtube.png" width="2%" alt="" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
-  <a href="https://www.facebook.com/ultralytics" style="text-decoration:none;">
+  <a href="https://www.tiktok.com/@ultralytics" style="text-decoration:none;">
-    <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-facebook.png" width="2%" alt="" /></a>
+    <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-tiktok.png" width="2%" alt="" /></a>
   <img src="https://github.com/ultralytics/assets/raw/main/social/logo-transparent.png" width="2%" alt="" />
   <a href="https://www.instagram.com/ultralytics/" style="text-decoration:none;">
     <img src="https://github.com/ultralytics/assets/raw/main/social/logo-social-instagram.png" width="2%" alt="" /></a>

ultralytics/__init__.py

@@ -1,6 +1,6 @@
 # Ultralytics YOLO 🚀, GPL-3.0 license
 
-__version__ = '8.0.55'
+__version__ = '8.0.56'
 
 from ultralytics.yolo.engine.model import YOLO
 from ultralytics.yolo.utils.checks import check_yolo as checks

ultralytics/models/v8/yolov8-p2.yaml

@@ -0,0 +1,54 @@
+# Ultralytics YOLO 🚀, GPL-3.0 license
+# YOLOv8 object detection model with P2-P5 outputs. For Usage examples see https://docs.ultralytics.com/tasks/detect
+
+# Parameters
+nc: 80  # number of classes
+scales: # model compound scaling constants, i.e. 'model=yolov8n.yaml' will call yolov8.yaml with scale 'n'
+  # [depth, width, max_channels]
+  n: [0.33, 0.25, 1024]
+  s: [0.33, 0.50, 1024]
+  m: [0.67, 0.75, 768]
+  l: [1.00, 1.00, 512]
+  x: [1.00, 1.25, 512]
+
+# YOLOv8.0 backbone
+backbone:
+  # [from, repeats, module, args]
+  - [-1, 1, Conv, [64, 3, 2]]  # 0-P1/2
+  - [-1, 1, Conv, [128, 3, 2]]  # 1-P2/4
+  - [-1, 3, C2f, [128, True]]
+  - [-1, 1, Conv, [256, 3, 2]]  # 3-P3/8
+  - [-1, 6, C2f, [256, True]]
+  - [-1, 1, Conv, [512, 3, 2]]  # 5-P4/16
+  - [-1, 6, C2f, [512, True]]
+  - [-1, 1, Conv, [1024, 3, 2]]  # 7-P5/32
+  - [-1, 3, C2f, [1024, True]]
+  - [-1, 1, SPPF, [1024, 5]]  # 9
+
+# YOLOv8.0-p2 head
+head:
+  - [-1, 1, nn.Upsample, [None, 2, 'nearest']]
+  - [[-1, 6], 1, Concat, [1]]  # cat backbone P4
+  - [-1, 3, C2f, [512]]  # 12
+
+  - [-1, 1, nn.Upsample, [None, 2, 'nearest']]
+  - [[-1, 4], 1, Concat, [1]]  # cat backbone P3
+  - [-1, 3, C2f, [256]]  # 15 (P3/8-small)
+
+  - [-1, 1, nn.Upsample, [None, 2, 'nearest']]
+  - [[-1, 2], 1, Concat, [1]]  # cat backbone P2
+  - [-1, 3, C2f, [128]]  # 18 (P2/4-xsmall)
+
+  - [-1, 1, Conv, [128, 3, 2]]
+  - [[-1, 15], 1, Concat, [1]]  # cat head P3
+  - [-1, 3, C2f, [256]]  # 21 (P3/8-small)
+
+  - [-1, 1, Conv, [256, 3, 2]]
+  - [[-1, 12], 1, Concat, [1]]  # cat head P4
+  - [-1, 3, C2f, [512]]  # 24 (P4/16-medium)
+
+  - [-1, 1, Conv, [512, 3, 2]]
+  - [[-1, 9], 1, Concat, [1]]  # cat head P5
+  - [-1, 3, C2f, [1024]]  # 27 (P5/32-large)
+
+  - [[18, 21, 24, 27], 1, Detect, [nc]]  # Detect(P2, P3, P4, P5)

ultralytics/tracker/trackers/basetrack.py

@@ -53,3 +53,7 @@ class BaseTrack:
 
     def mark_removed(self):
         self.state = TrackState.Removed
+
+    @staticmethod
+    def reset_id():
+        BaseTrack._count = 0

ultralytics/tracker/trackers/byte_tracker.py

@@ -168,6 +168,7 @@ class BYTETracker:
         self.args = args
         self.max_time_lost = int(frame_rate / 30.0 * args.track_buffer)
         self.kalman_filter = self.get_kalmanfilter()
+        self.reset_id()
 
     def update(self, results, img=None):
         self.frame_id += 1
@@ -299,6 +300,9 @@ class BYTETracker:
     def multi_predict(self, tracks):
         STrack.multi_predict(tracks)
 
+    def reset_id(self):
+        STrack.reset_id()
+
     @staticmethod
     def joint_stracks(tlista, tlistb):
         exists = {}

ultralytics/yolo/data/dataloaders/stream_loaders.py

@@ -284,6 +284,7 @@ class LoadPilAndNumpy:
     def __init__(self, im0, imgsz=640, stride=32, auto=True, transforms=None):
         if not isinstance(im0, list):
             im0 = [im0]
+        self.paths = [getattr(im, 'filename', f'image{i}.jpg') for i, im in enumerate(im0)]
         self.im0 = [self._single_check(im) for im in im0]
         self.imgsz = imgsz
         self.stride = stride
@@ -291,7 +292,6 @@ class LoadPilAndNumpy:
         self.transforms = transforms
         self.mode = 'image'
         # generate fake paths
-        self.paths = [getattr(im, 'filename', f'image{i}.jpg') for i, im in enumerate(self.im0)]
         self.bs = len(self.im0)
 
     @staticmethod

ultralytics/yolo/data/dataset.py

@@ -125,7 +125,10 @@ class YOLODataset(BaseDataset):
         self.label_files = img2label_paths(self.im_files)
         cache_path = Path(self.label_files[0]).parent.with_suffix('.cache')
         try:
+            import gc
+            gc.disable()  # reduce pickle load time https://github.com/ultralytics/ultralytics/pull/1585
             cache, exists = np.load(str(cache_path), allow_pickle=True).item(), True  # load dict
+            gc.enable()
             assert cache['version'] == self.cache_version  # matches current version
             assert cache['hash'] == get_hash(self.label_files + self.im_files)  # identical hash
         except (FileNotFoundError, AssertionError, AttributeError):

ultralytics/yolo/engine/results.py

@@ -129,13 +129,14 @@ class Results:
         annotator = Annotator(deepcopy(self.orig_img), line_width, font_size, font, pil, example)
         boxes = self.boxes
         masks = self.masks
-        logits = self.probs
+        probs = self.probs
         names = self.names
+        hide_labels, hide_conf = False, not show_conf
         if boxes is not None:
             for d in reversed(boxes):
-                cls, conf = d.cls.squeeze(), d.conf.squeeze()
+                c, conf, id = int(d.cls), float(d.conf), None if d.id is None else int(d.id.item())
-                c = int(cls)
+                name = ('' if id is None else f'id:{id} ') + names[c]
-                label = (f'{names[c]}' if names else f'{c}') + (f'{conf:.2f}' if show_conf else '')
+                label = None if hide_labels else (name if hide_conf else f'{name} {conf:.2f}')
                 annotator.box_label(d.xyxy.squeeze(), label, color=colors(c, True))
 
         if masks is not None:
@@ -143,10 +144,10 @@ class Results:
             im = F.resize(im.contiguous(), masks.data.shape[1:]) / 255
             annotator.masks(masks.data, colors=[colors(x, True) for x in boxes.cls], im_gpu=im)
 
-        if logits is not None:
+        if probs is not None:
-            n5 = min(len(self.names), 5)
+            n5 = min(len(names), 5)
-            top5i = logits.argsort(0, descending=True)[:n5].tolist()  # top 5 indices
+            top5i = probs.argsort(0, descending=True)[:n5].tolist()  # top 5 indices
-            text = f"{', '.join(f'{names[j] if names else j} {logits[j]:.2f}' for j in top5i)}, "
+            text = f"{', '.join(f'{names[j] if names else j} {probs[j]:.2f}' for j in top5i)}, "
             annotator.text((32, 32), text, txt_color=(255, 255, 255))  # TODO: allow setting colors
 
         return np.asarray(annotator.im) if annotator.pil else annotator.im

ultralytics/yolo/utils/__init__.py

@@ -445,7 +445,7 @@ def get_user_config_dir(sub_dir='Ultralytics'):
     return path
 
 
-USER_CONFIG_DIR = get_user_config_dir()  # Ultralytics settings dir
+USER_CONFIG_DIR = os.getenv('YOLO_CONFIG_DIR', get_user_config_dir())  # Ultralytics settings dir
 
 
 def emojis(string=''):

ultralytics/yolo/utils/checks.py

@@ -21,7 +21,7 @@ import torch
 from matplotlib import font_manager
 
 from ultralytics.yolo.utils import (AUTOINSTALL, LOGGER, ONLINE, ROOT, USER_CONFIG_DIR, TryExcept, colorstr, downloads,
-                                    emojis, is_colab, is_docker, is_jupyter, is_online, is_pip_package)
+                                    emojis, is_colab, is_docker, is_kaggle, is_online, is_pip_package)
 
 
 def is_ascii(s) -> bool:
@@ -292,8 +292,7 @@ def check_yaml(file, suffix=('.yaml', '.yml'), hard=True):
 def check_imshow(warn=False):
     # Check if environment supports image displays
     try:
-        assert not is_jupyter()
+        assert not any((is_colab(), is_kaggle(), is_docker()))
-        assert not is_docker()
         cv2.imshow('test', np.zeros((1, 1, 3)))
         cv2.waitKey(1)
         cv2.destroyAllWindows()

ultralytics/yolo/utils/torch_utils.py

@@ -27,6 +27,7 @@ WORLD_SIZE = int(os.getenv('WORLD_SIZE', 1))
 TORCH_1_9 = check_version(torch.__version__, '1.9.0')
 TORCH_1_11 = check_version(torch.__version__, '1.11.0')
 TORCH_1_12 = check_version(torch.__version__, '1.12.0')
+TORCH_2_X = check_version(torch.__version__, minimum='2.0')
 
 
 @contextmanager
@@ -95,7 +96,8 @@ def select_device(device='', batch=0, newline=False, verbose=True):
             p = torch.cuda.get_device_properties(i)
             s += f"{'' if i == 0 else space}CUDA:{d} ({p.name}, {p.total_memory / (1 << 20):.0f}MiB)\n"  # bytes to MB
         arg = 'cuda:0'
-    elif mps and getattr(torch, 'has_mps', False) and torch.backends.mps.is_available():  # prefer MPS if available
+    elif mps and getattr(torch, 'has_mps', False) and torch.backends.mps.is_available() and TORCH_2_X:
+        # prefer MPS if available
         s += 'MPS\n'
         arg = 'mps'
     else:  # revert to CPU

ultralytics/yolo/v8/detect/train.py

@@ -134,6 +134,7 @@ class Loss:
         else:
             i = targets[:, 0]  # image index
             _, counts = i.unique(return_counts=True)
+            counts = counts.to(dtype=torch.int32)
             out = torch.zeros(batch_size, counts.max(), 5, device=self.device)
             for j in range(batch_size):
                 matches = i == j

ultralytics/yolo/v8/detect/val.py

@@ -108,8 +108,9 @@ class DetectionValidator(BaseValidator):
             # Save
             if self.args.save_json:
                 self.pred_to_json(predn, batch['im_file'][si])
-            # if self.args.save_txt:
+            if self.args.save_txt:
-            #    save_one_txt(predn, save_conf, shape, file=save_dir / 'labels' / f'{path.stem}.txt')
+                file = self.save_dir / 'labels' / f'{Path(batch["im_file"][si]).stem}.txt'
+                self.save_one_txt(predn, self.args.save_conf, shape, file)
 
     def finalize_metrics(self, *args, **kwargs):
         self.metrics.speed = self.speed
@@ -197,6 +198,14 @@ class DetectionValidator(BaseValidator):
                     fname=self.save_dir / f'val_batch{ni}_pred.jpg',
                     names=self.names)  # pred
 
+    def save_one_txt(self, predn, save_conf, shape, file):
+        gn = torch.tensor(shape)[[1, 0, 1, 0]]  # normalization gain whwh
+        for *xyxy, conf, cls in predn.tolist():
+            xywh = (ops.xyxy2xywh(torch.tensor(xyxy).view(1, 4)) / gn).view(-1).tolist()  # normalized xywh
+            line = (cls, *xywh, conf) if save_conf else (cls, *xywh)  # label format
+            with open(file, 'a') as f:
+                f.write(('%g ' * len(line)).rstrip() % line + '\n')
+
     def pred_to_json(self, predn, filename):
         stem = Path(filename).stem
         image_id = int(stem) if stem.isnumeric() else stem

ultralytics/yolo/v8/segment/train.py

@@ -79,7 +79,7 @@ class SegLoss(Loss):
         # targets
         try:
             batch_idx = batch['batch_idx'].view(-1, 1)
-            targets = torch.cat((batch_idx, batch['cls'].view(-1, 1), batch['bboxes']), 1)
+            targets = torch.cat((batch_idx, batch['cls'].view(-1, 1), batch['bboxes'].to(dtype)), 1)
             targets = self.preprocess(targets.to(self.device), batch_size, scale_tensor=imgsz[[1, 0, 1, 0]])
             gt_labels, gt_bboxes = targets.split((1, 4), 2)  # cls, xyxy
             mask_gt = gt_bboxes.sum(2, keepdim=True).gt_(0)