3588适配

detect.py

@@ -15,7 +15,7 @@ from utils.plots import plot_one_box
 from utils.torch_utils import select_device, load_classifier, time_synchronized
 
 
-def detect(opt, save_img=False):
+def detect(opt, model, stride, save_img=False):
     source, weights, view_img, save_txt, imgsz = opt.source, opt.weights, opt.view_img, opt.save_txt, opt.img_size
     save_img = not opt.nosave and not source.endswith('.txt')  # save inference images
     webcam = source.isnumeric() or source.endswith('.txt') or source.lower().startswith(
@@ -31,12 +31,15 @@ def detect(opt, save_img=False):
     half = device.type != 'cpu'  # half precision only supported on CUDA
 
     # Load model
-    model = attempt_load(weights, map_location=device)  # load FP32 model
-    stride = int(model.stride.max())  # model stride
+#    model = attempt_load(weights, map_location=device)  # load FP32 model
+#    stride = int(model.stride.max())  # model stride
     imgsz = check_img_size(imgsz, s=stride)  # check img_size
-    if half:
-        model.half()  # to FP16
-    model.eval()
+#    if half:
+#        model.half()  # to FP16
+#    model.eval()
+    model = model
+
+
     # Second-stage classifier
     classify = False
     if classify: