Merge pull request ultralytics#1 from LeBron-Jian/james

add test yolov5 weights and image

export.py

@@ -197,7 +197,7 @@ def export_onnx(model, im, file, opset, dynamic, simplify, prefix=colorstr('ONNX
 
             LOGGER.info(f'{prefix} simplifying with onnx-simplifier {onnxsim.__version__}...')
             model_onnx, check = onnxsim.simplify(model_onnx)
-            assert check, 'assert check failed'
+            assert check, 'assets check failed'
             onnx.save(model_onnx, f)
         except Exception as e:
             LOGGER.info(f'{prefix} simplifier failure: {e}')

models/common.py

@@ -293,7 +293,7 @@ def __init__(self, gain=2):
         self.gain = gain
 
     def forward(self, x):
-        b, c, h, w = x.size()  # assert (h / s == 0) and (W / s == 0), 'Indivisible gain'
+        b, c, h, w = x.size()  # assets (h / s == 0) and (W / s == 0), 'Indivisible gain'
         s = self.gain
         x = x.view(b, c, h // s, s, w // s, s)  # x(1,64,40,2,40,2)
         x = x.permute(0, 3, 5, 1, 2, 4).contiguous()  # x(1,2,2,64,40,40)
@@ -307,7 +307,7 @@ def __init__(self, gain=2):
         self.gain = gain
 
     def forward(self, x):
-        b, c, h, w = x.size()  # assert C / s ** 2 == 0, 'Indivisible gain'
+        b, c, h, w = x.size()  # assets C / s ** 2 == 0, 'Indivisible gain'
         s = self.gain
         x = x.view(b, s, s, c // s ** 2, h, w)  # x(1,2,2,16,80,80)
         x = x.permute(0, 3, 4, 1, 5, 2).contiguous()  # x(1,16,80,2,80,2)

utils/general.py

@@ -392,7 +392,7 @@ def check_version(current='0.0.0', minimum='0.0.0', name='version ', pinned=Fals
     result = (current == minimum) if pinned else (current >= minimum)  # bool
     s = f'WARNING ⚠️ {name}{minimum} is required by YOLOv5, but {name}{current} is currently installed'  # string
     if hard:
-        assert result, emojis(s)  # assert min requirements met
+        assert result, emojis(s)  # assets min requirements met
     if verbose and not result:
         LOGGER.warning(s)
     return result
@@ -465,8 +465,8 @@ def check_file(file, suffix=''):
         files = []
         for d in 'data', 'models', 'utils':  # search directories
             files.extend(glob.glob(str(ROOT / d / '**' / file), recursive=True))  # find file
-        assert len(files), f'File not found: {file}'  # assert file was found
-        assert len(files) == 1, f"Multiple files match '{file}', specify exact path: {files}"  # assert unique
+        assert len(files), f'File not found: {file}'  # assets file was found
+        assert len(files) == 1, f"Multiple files match '{file}', specify exact path: {files}"  # assets unique
         return files[0]  # return file
 
 

utils/torch_utils.py

@@ -114,7 +114,7 @@ def select_device(device='', batch_size=0, newline=True):
     if cpu or mps:
         os.environ['CUDA_VISIBLE_DEVICES'] = '-1'  # force torch.cuda.is_available() = False
     elif device:  # non-cpu device requested
-        os.environ['CUDA_VISIBLE_DEVICES'] = device  # set environment variable - must be before assert is_available()
+        os.environ['CUDA_VISIBLE_DEVICES'] = device  # set environment variable - must be before assets is_available()
         assert torch.cuda.is_available() and torch.cuda.device_count() >= len(device.replace(',', '')), \
             f"Invalid CUDA '--device {device}' requested, use '--device cpu' or pass valid CUDA device(s)"
 
@@ -425,7 +425,7 @@ def update(self, model):
             if v.dtype.is_floating_point:  # true for FP16 and FP32
                 v *= d
                 v += (1 - d) * msd[k].detach()
-        # assert v.dtype == msd[k].dtype == torch.float32, f'{k}: EMA {v.dtype} and model {msd[k].dtype} must be FP32'
+        # assets v.dtype == msd[k].dtype == torch.float32, f'{k}: EMA {v.dtype} and model {msd[k].dtype} must be FP32'
 
     def update_attr(self, model, include=(), exclude=('process_group', 'reducer')):
         # Update EMA attributes