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Update app.py
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app.py
CHANGED
@@ -28,6 +28,7 @@ def detect(opt, save_img=False):
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# from utils.plots import plot_one_box
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# from utils.torch_utils import select_device, load_classifier, time_synchronized, TracedModel
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from yolov7_package.models.experimental import attempt_load
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from yolov7_package.utils.general import check_img_size, check_requirements, check_imshow, non_max_suppression, apply_classifier, \
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scale_coords, xyxy2xywh, strip_optimizer, set_logging, increment_path
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@@ -50,7 +51,9 @@ def detect(opt, save_img=False):
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half = device.type != 'cpu' # half precision only supported on CUDA
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# Load model
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model = attempt_load(weights, map_location=device) # load FP32 model
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stride = int(model.stride.max()) # model stride
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imgsz = check_img_size(imgsz, s=stride) # check img_size
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# from utils.plots import plot_one_box
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# from utils.torch_utils import select_device, load_classifier, time_synchronized, TracedModel
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from yolov7_package import Yolov7Detector
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from yolov7_package.models.experimental import attempt_load
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from yolov7_package.utils.general import check_img_size, check_requirements, check_imshow, non_max_suppression, apply_classifier, \
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scale_coords, xyxy2xywh, strip_optimizer, set_logging, increment_path
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half = device.type != 'cpu' # half precision only supported on CUDA
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# Load model
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det = Yolov7Detector(weights=weights, traced=False)
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model = attempt_load(weights, map_location=device) # load FP32 model
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model = TracedModel(model, device, 640)
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stride = int(model.stride.max()) # model stride
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imgsz = check_img_size(imgsz, s=stride) # check img_size
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