update README - image size #17

Author: Borda

README.md

@@ -45,11 +45,13 @@ For more model and configuration please see  [YOLO website](http://pjreddie.com/
        --path_weights ./model_data/yolo.h5 \
        --path_anchors ./model_data/yolo_anchors.csv \
        --path_classes ./model_data/coco_classes.txt \
+       --model_image_size 608 608 \
        --path_output ./results \
        --path_image ./model_data/bike-car-dog.jpg \
        --path_video person.mp4
     ```
     For Full YOLOv3, just do in a similar way, just specify model path and anchor path with `--path_weights <model_file>` and `--path_anchors <anchor_file>`.
+    Note `model_image_size` is depending on used model, see width and height in model config `*.cfg`. Expected values are ` 608 608` for full YOLO and and `416 416` for Tiny YOLO.
 4. MultiGPU usage: use `--nb_gpu N` to use N GPUs. It is passed to the Keras [multi_gpu_model()](https://keras.io/utils/#multi_gpu_model).
 
 ---

scripts/detection.py

@@ -40,8 +40,8 @@ def arg_params_yolo():
                         help='path to model weight file')
     parser.add_argument('-a', '--path_anchors', type=str,
                         help='path to anchor definitions')
-    parser.add_argument('--model_image_size', type=int, nargs=2,
-                        help='input image size for the model')
+    parser.add_argument('--model_image_size', type=int, nargs=2, required=False,
+                        help='input image size for the model', default=(None, None))
     parser.add_argument('-c', '--path_classes', type=str,
                         help='path to class definitions')
     parser.add_argument('--nb_gpu', type=int, help='Number of GPU to use',

yolo3/yolo.py

@@ -59,7 +59,7 @@ def get_defaults(cls, name):
             logging.warning('Unrecognized attribute name "%s"', name)
         return cls._DEFAULT_PARAMS.get(name)
 
-    def __init__(self, weights_path, anchors_path, classes_path, model_image_size,
+    def __init__(self, weights_path, anchors_path, classes_path, model_image_size=(None, None),
                  score=0.3, iou=0.45, nb_gpu=1, **kwargs):
         """
 
@@ -165,7 +165,7 @@ def _generate_class_colors(self):
     def detect_image(self, image):
         start = time.time()
 
-        if self.model_image_size != (None, None):
+        if isinstance(self.model_image_size, (list, tuple, set)) and all(self.model_image_size):
             assert self.model_image_size[0] % 32 == 0, 'Multiples of 32 required'
             assert self.model_image_size[1] % 32 == 0, 'Multiples of 32 required'
             boxed_image = letterbox_image(image, tuple(reversed(self.model_image_size)))