support depoly infer for fcos (#1330)

deploy/python/infer.py

@@ -74,7 +74,7 @@ class Resize(object):
         self.arch = arch
         self.use_cv2 = use_cv2
         self.interp = interp
-        self.scale_set = {'RCNN', 'RetinaNet'}
+        self.scale_set = {'RCNN', 'RetinaNet', 'FCOS'}
 
     def __call__(self, im, im_info):
         """
@@ -259,7 +259,7 @@ def create_inputs(im, im_info, model_arch='YOLO'):
         scale = scale_x
         im_info = np.array([resize_shape + [scale]]).astype('float32')
         inputs['im_info'] = im_info
-    elif 'RCNN' in model_arch:
+    elif ('RCNN' in model_arch) or ('FCOS' in model_arch):
         scale = scale_x
         im_info = np.array([resize_shape + [scale]]).astype('float32')
         im_shape = np.array([origin_shape + [1.]]).astype('float32')
@@ -276,7 +276,15 @@ class Config():
     Args:
         model_dir (str): root path of model.yml
     """
-    support_models = ['YOLO', 'SSD', 'RetinaNet', 'RCNN', 'Face', 'TTF']
+    support_models = [
+        'YOLO',
+        'SSD',
+        'RetinaNet',
+        'RCNN',
+        'Face',
+        'TTF',
+        'FCOS',
+    ]
 
     def __init__(self, model_dir):
         # parsing Yaml config for Preprocess
@@ -566,15 +574,19 @@ def predict_image():
             output_dir=FLAGS.output_dir)
 
 
-def predict_video():
+def predict_video(camera_id):
     detector = Detector(
         FLAGS.model_dir, use_gpu=FLAGS.use_gpu, run_mode=FLAGS.run_mode)
+    if camera_id != -1:
+        capture = cv2.VideoCapture(camera_id)
+        video_name = 'output.mp4'
+    else:
         capture = cv2.VideoCapture(FLAGS.video_file)
+        video_name = os.path.split(FLAGS.video_file)[-1]
     fps = 30
     width = int(capture.get(cv2.CAP_PROP_FRAME_WIDTH))
     height = int(capture.get(cv2.CAP_PROP_FRAME_HEIGHT))
     fourcc = cv2.VideoWriter_fourcc(*'mp4v')
-    video_name = os.path.split(FLAGS.video_file)[-1]
     if not os.path.exists(FLAGS.output_dir):
         os.makedirs(FLAGS.output_dir)
     out_path = os.path.join(FLAGS.output_dir, video_name)
@@ -594,6 +606,10 @@ def predict_video():
             mask_resolution=detector.config.mask_resolution)
         im = np.array(im)
         writer.write(im)
+        if camera_id != -1:
+            cv2.imshow('Mask Detection', im)
+            if cv2.waitKey(1) & 0xFF == ord('q'):
+                break
     writer.release()
 
 
@@ -617,6 +633,11 @@ if __name__ == '__main__':
         "--image_file", type=str, default='', help="Path of image file.")
     parser.add_argument(
         "--video_file", type=str, default='', help="Path of video file.")
+    parser.add_argument(
+        "--camera_id",
+        type=int,
+        default=-1,
+        help="device id of camera to predict.")
     parser.add_argument(
         "--run_mode",
         type=str,
@@ -647,5 +668,5 @@ if __name__ == '__main__':
         assert "Cannot predict image and video at the same time"
     if FLAGS.image_file != '':
         predict_image()
-    if FLAGS.video_file != '':
-        predict_video()
+    if FLAGS.video_file != '' or FLAGS.camera_id != -1:
+        predict_video(FLAGS.camera_id)