Add requirements check and improve code

Author: RizwanMunawar

README.md

@@ -101,7 +101,6 @@
 |-------------------------|-------------|-------------------------------|---------------------------------------------------------------------|
 | `--weights`             | `str`       | `yolov7.pt`                   | Path(s) to model weights (`.pt` file).                              |
 | `--download`            | `flag`      | `False`                       | Download model weights automatically.                               |
-| `--no-download`         | `flag`      | `False`                       | Do not download model weights if they already exist.                |
 | `--source`              | `str`       | `None`                        | Source for inference (file, folder, or `0` for webcam).             |
 | `--img-size`            | `int`       | `640`                         | Inference image size in pixels.                                     |
 | `--conf-thres`          | `float`     | `0.25`                        | Object confidence threshold.                                        |

assets/demo.mp4

@@ -195,6 +195,19 @@ def detect():
     opt = parser.parse_args()
     print(opt)
 
+    check_requirements([
+        "matplotlib>=3.2.2",
+        "numpy>=1.18.5",
+        "opencv-python>=4.1.1",
+        "Pillow>=7.1.2",
+        "PyYAML>=5.3.1",
+        "requests>=2.23.0",
+        "scipy>=1.4.1",
+        "torch>=1.7.0,!=1.12.0",
+        "torchvision>=0.8.1,!=0.13.0",
+        "tqdm>=4.41.0",
+        "protobuf==4.25.8",
+    ])
     if not os.path.exists(opt.weights[0]):
         print('⚠️ Model weights not found. Attempting to download now...')
         download('./')

detect.py

@@ -7,7 +7,7 @@
 
 from models.experimental import attempt_load
 from utils.datasets import LoadStreams, LoadImages
-from utils.general import check_img_size, \
+from utils.general import check_img_size, check_requirements, \
                 check_imshow, non_max_suppression, apply_classifier, \
                 scale_coords, strip_optimizer, set_logging, \
                 increment_path
@@ -281,7 +281,6 @@ def detect():
     parser = argparse.ArgumentParser()
     parser.add_argument('--weights', nargs='+', type=str, default='yolov7.pt', help='model.pt path(s)')
     parser.add_argument('--download', action='store_true', help='download model weights automatically')
-    parser.add_argument('--no-download', dest='download', action='store_false',help='not download model weights if already exist')
     parser.add_argument('--source', type=str, default=None, help='source')  # file/folder, 0 for webcam
     parser.add_argument('--img-size', type=int, default=640, help='inference size (pixels)')
     parser.add_argument('--conf-thres', type=float, default=0.25, help='object confidence threshold')
@@ -306,8 +305,22 @@ def detect():
     parser.set_defaults(download=True)
     opt = parser.parse_args()
     print(opt)
-    #check_requirements(exclude=('pycocotools', 'thop'))
-    if opt.download and not os.path.exists(''.join(opt.weights)):
+    check_requirements([
+        "matplotlib>=3.2.2",
+        "numpy>=1.18.5",
+        "opencv-python>=4.1.1",
+        "Pillow>=7.1.2",
+        "PyYAML>=5.3.1",
+        "requests>=2.23.0",
+        "scipy>=1.4.1",
+        "torch>=1.7.0,!=1.12.0",
+        "torchvision>=0.8.1,!=0.13.0",
+        "tqdm>=4.41.0",
+        "protobuf==4.25.8",
+        "filterpy",
+        "scikit-image"
+    ])
+    if not os.path.exists(''.join(opt.weights)):
         print('Model weights not found. Attempting to download now...')
         download('./')
 

detect_and_track.py

@@ -21,11 +21,9 @@ def forward(self, x, augment=False):
 
 def attempt_load(weights, map_location=None):
     # Loads an ensemble of models weights=[a,b,c] or a single model weights=[a] or weights=a
-    from packaging import version
-    weights_only = False if version.parse(torch.__version__) >= version.parse("2.6") else True
     model = Ensemble()
     for w in weights if isinstance(weights, list) else [weights]:
-        ckpt = torch.load(w, map_location=map_location, weights_only=weights_only)  # load
+        ckpt = torch.load(w, map_location=map_location, weights_only=False)  # load with weights only=False  https://pytorch.org/docs/stable/generated/torch.load.html
         model.append(ckpt['ema' if ckpt.get('ema') else 'model'].float().fuse().eval())  # FP32 model
 
     # Compatibility updates

models/experimental.py

@@ -89,17 +89,6 @@ def convert(self, z):
         return box, score
 
 
-def check_anchor_order(m):
-    # Check anchor order against stride order for YOLO Detect() module m, and correct if necessary
-    a = m.anchor_grid.prod(-1).view(-1)  # anchor area
-    da = a[-1] - a[0]  # delta a
-    ds = m.stride[-1] - m.stride[0]  # delta s
-    if da.sign() != ds.sign():  # same order
-        print('Reversing anchor order')
-        m.anchors[:] = m.anchors.flip(0)
-        m.anchor_grid[:] = m.anchor_grid.flip(0)
-
-
 class Model(nn.Module):
     def __init__(self, cfg='yolor-csp-c.yaml', ch=3, nc=None, anchors=None):  # model, input channels, number of classes
         super(Model, self).__init__()

models/yolo.py

@@ -62,7 +62,7 @@ def git_describe(path=Path(__file__).parent):  # path must be a directory
 
 def select_device(device='', batch_size=None):
     # device = 'cpu' or '0' or '0,1,2,3'
-    s = f'YOLOv7 🚀 {git_describe() or date_modified()} torch {torch.__version__}'  # string
+    s = f'YOLOv7 🚀  {git_describe() or date_modified()} torch {torch.__version__}'  # string
     cpu = device.lower() == 'cpu'
     if cpu:
         os.environ['CUDA_VISIBLE_DEVICES'] = '-1'  # force torch.cuda.is_available() = False