ultralytics 8.0.88 Pose TFLite model fix (#2261)

ultralytics/__init__.py

@@ -1,6 +1,6 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
-__version__ = '8.0.87'
+__version__ = '8.0.88'
 
 from ultralytics.hub import start
 from ultralytics.yolo.engine.model import YOLO

ultralytics/hub/utils.py

@@ -161,7 +161,7 @@ class Events:
         Initializes the Events object with default values for events, rate_limit, and metadata.
         """
         self.events = []  # events list
-        self.rate_limit = 10.0  # rate limit (seconds)
+        self.rate_limit = 60.0  # rate limit (seconds)
         self.t = 0.0  # rate limit timer (seconds)
         self.metadata = {
             'cli': Path(sys.argv[0]).name == 'yolo',
@@ -204,7 +204,9 @@ class Events:
 
         # Time is over rate limiter, send now
         data = {'client_id': SETTINGS['uuid'], 'events': self.events}  # SHA-256 anonymized UUID hash and events list
-        smart_request('post', self.url, json=data, retry=0, code=3)  # equivalent to requests.post(self.url, json=data)
+
+        # POST equivalent to requests.post(self.url, json=data)
+        smart_request('post', self.url, json=data, retry=0, verbose=False)
 
         # Reset events and rate limit timer
         self.events = []

ultralytics/nn/modules.py

@@ -541,18 +541,25 @@ class Pose(Detect):
         x = self.detect(self, x)
         if self.training:
             return x, kpt
-        pred_kpt = self.kpts_decode(kpt)
+        pred_kpt = self.kpts_decode(bs, kpt)
         return torch.cat([x, pred_kpt], 1) if self.export else (torch.cat([x[0], pred_kpt], 1), (x[1], kpt))
 
-    def kpts_decode(self, kpts):
+    def kpts_decode(self, bs, kpts):
         """Decodes keypoints."""
         ndim = self.kpt_shape[1]
-        y = kpts.clone()
-        if ndim == 3:
-            y[:, 2::3].sigmoid_()  # inplace sigmoid
-        y[:, 0::ndim] = (y[:, 0::ndim] * 2.0 + (self.anchors[0] - 0.5)) * self.strides
-        y[:, 1::ndim] = (y[:, 1::ndim] * 2.0 + (self.anchors[1] - 0.5)) * self.strides
-        return y
+        if self.export:  # required for TFLite export to avoid 'PLACEHOLDER_FOR_GREATER_OP_CODES' bug
+            y = kpts.view(bs, *self.kpt_shape, -1)
+            a = (y[:, :, :2] * 2.0 + (self.anchors - 0.5)) * self.strides
+            if ndim == 3:
+                a = torch.cat((a, y[:, :, 1:2].sigmoid()), 2)
+            return a.view(bs, self.nk, -1)
+        else:
+            y = kpts.clone()
+            if ndim == 3:
+                y[:, 2::3].sigmoid_()  # inplace sigmoid
+            y[:, 0::ndim] = (y[:, 0::ndim] * 2.0 + (self.anchors[0] - 0.5)) * self.strides
+            y[:, 1::ndim] = (y[:, 1::ndim] * 2.0 + (self.anchors[1] - 0.5)) * self.strides
+            return y
 
 
 class Classify(nn.Module):