updates

detect.py

@@ -9,8 +9,7 @@ from utils.utils import *
 def detect(save_txt=False, save_img=False, view_img=False):
     img_size = (320, 192) if ONNX_EXPORT else opt.img_size  # (320, 192) or (416, 256) or (608, 352) for (height, width)
     out, source, weights, half = opt.output, opt.source, opt.weights, opt.half
-    webcam = source == '0' or source.startswith('rtsp') or source.startswith('http')
-    streams = 'streams' in source and source.endswith('.txt')
+    webcam = source == '0' or source.startswith('rtsp') or source.startswith('http') or source.endswith('.txt')
 
     # Initialize
     device = torch_utils.select_device(device='cpu' if ONNX_EXPORT else opt.device)
@@ -47,13 +46,10 @@ def detect(save_txt=False, save_img=False, view_img=False):
 
     # Set Dataloader
     vid_path, vid_writer = None, None
-    if streams:
-        view_img = False
+    if webcam:
+        view_img = True
         torch.backends.cudnn.benchmark = True  # set True to speed up constant image size inference
         dataset = LoadStreams(source, img_size=img_size, half=half)
-    elif webcam:
-        view_img = True
-        dataset = LoadWebcam(source, img_size=img_size, half=half)
     else:
         save_img = True
         dataset = LoadImages(source, img_size=img_size, half=half)
@@ -74,7 +70,7 @@ def detect(save_txt=False, save_img=False, view_img=False):
         pred, _ = model(img)
 
         for i, det in enumerate(non_max_suppression(pred, opt.conf_thres, opt.nms_thres)):  # detections per image
-            if streams:  # batch_size > 1
+            if webcam:  # batch_size >= 1
                 p, s, im0 = path[i], '%g: ' % i, im0s[i]
             else:
                 p, s, im0 = path, '', im0s

utils/datasets.py

@@ -186,11 +186,13 @@ class LoadWebcam:  # for inference
 
 
 class LoadStreams:  # multiple IP or RTSP cameras
-    def __init__(self, path='streams.txt', img_size=416, half=False):
+    def __init__(self, sources='streams.txt', img_size=416, half=False):
         self.img_size = img_size
         self.half = half  # half precision fp16 images
-        with open(path, 'r') as f:
-            sources = [x.strip() for x in f.read().splitlines() if len(x.strip())]
+
+        if os.path.isfile(sources):
+            with open(sources, 'r') as f:
+                sources = [x.strip() for x in f.read().splitlines() if len(x.strip())]
 
         n = len(sources)
         self.imgs = [None] * n
@@ -208,7 +210,7 @@ class LoadStreams:  # multiple IP or RTSP cameras
             thread.start()
 
         print('')  # newline
-        time.sleep(0.5)
+        time.sleep(0.5)  # allow connections to start
 
     def update(self, index, cap):
         # Read next stream frame in a daemon thread