updates
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@ -120,9 +120,13 @@ class LoadWebcam: # for inference
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def __init__(self, img_size=416, half=False):
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self.img_size = img_size
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self.half = half # half precision fp16 images
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self.cam = cv2.VideoCapture(0) # local camera
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# self.cam = cv2.VideoCapture('rtsp://192.168.1.64/1') # IP camera
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# self.cam = cv2.VideoCapture('rtsp://username:password@192.168.1.64/1') # IP camera with login
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pipe = 0 # local camera
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# pipe = 'rtsp://192.168.1.64/1' # IP camera
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# pipe = 'rtsp://username:password@192.168.1.64/1' # IP camera with login
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# pipe = '"rtspsrc location="rtsp://username:password@192.168.1.64/1" latency=10 ! appsink' # GStreamer https://answers.opencv.org/question/215996/changing-gstreamer-pipeline-to-opencv-in-pythonsolved/
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self.cap = cv2.VideoCapture(pipe) # video capture object
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def __iter__(self):
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self.count = -1
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@ -135,7 +139,7 @@ class LoadWebcam: # for inference
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raise StopIteration
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# Read image
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ret_val, img0 = self.cam.read()
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ret_val, img0 = self.cap.read()
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assert ret_val, 'Webcam Error'
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img_path = 'webcam_%g.jpg' % self.count
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img0 = cv2.flip(img0, 1) # flip left-right
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@ -156,7 +160,8 @@ class LoadWebcam: # for inference
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class LoadImagesAndLabels(Dataset): # for training/testing
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def __init__(self, path, img_size=416, batch_size=16, augment=False, hyp=None, rect=True, image_weights=False, cache_images=False):
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def __init__(self, path, img_size=416, batch_size=16, augment=False, hyp=None, rect=True, image_weights=False,
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cache_images=False):
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path = str(Path(path)) # os-agnostic
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with open(path, 'r') as f:
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self.img_files = [x.replace('/', os.sep) for x in f.read().splitlines() # os-agnostic
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@ -775,7 +775,7 @@ def plot_results(start=0, stop=0): # from utils.utils import *; plot_results()
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ax[i].get_shared_y_axes().join(ax[i], ax[i - 5])
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fig.tight_layout()
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ax[4].legend()
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ax[0].legend()
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fig.savefig('results.png', dpi=200)
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