remove RTMDet-v1-Pico

models/detectors/rtmdet_v1/README.md

@@ -2,7 +2,6 @@
 
 |   Model    | Scale | Batch | AP<sup>test<br>0.5:0.95 | AP<sup>test<br>0.5 | AP<sup>val<br>0.5:0.95 | AP<sup>val<br>0.5 | FLOPs<br><sup>(G) | Params<br><sup>(M) | Weight |
 |------------|-------|-------|-------------------------|--------------------|------------------------|-------------------|-------------------|--------------------|--------|
-| RTMDetv1-P |  640  | 8xb16 |                         |                    |                        |                   |      4.4          |        1.5         |  |
 | RTMDetv1-N |  640  | 8xb16 |                         |                    |                        |                   |      9.1          |        2.4         |  |
 | RTMDetv1-T |  640  | 8xb16 |         40.5            |        59.1        |          40.3          |        59.1       |      19.0         |        5.1         | [ckpt](https://github.com/yjh0410/PyTorch_YOLO_Tutorial/releases/download/yolo_tutorial_ckpt/RTMDetv1_t_coco.pth) |
 | RTMDetv1-S |  640  | 8xb16 |         43.6            |        62.6        |          43.3          |        62.6       |      33.6         |        9.0         | [ckpt](https://github.com/yjh0410/PyTorch_YOLO_Tutorial/releases/download/yolo_tutorial_ckpt/RTMDetv1_s_coco.pth) |

models/detectors/rtmdet_v1/rtmdet_v1_backbone.py

@@ -8,7 +8,6 @@ except:
 
 
 model_urls = {
-    'elannet_pico': "https://github.com/yjh0410/image_classification_pytorch/releases/download/weight/elannet_pico.pth",
     'elannet_nano': "https://github.com/yjh0410/image_classification_pytorch/releases/download/weight/elannet_nano.pth",
     'elannet_tiny': "https://github.com/yjh0410/image_classification_pytorch/releases/download/weight/elannet_tiny.pth",
     'elannet_small': "https://github.com/yjh0410/image_classification_pytorch/releases/download/weight/elannet_small.pth",
@@ -111,9 +110,7 @@ def build_backbone(cfg, pretrained=False):
         )
     # check whether to load imagenet pretrained weight
     if pretrained:
-        if cfg['width'] == 0.25 and cfg['depth'] == 0.34 and cfg['bk_dpw']:
-            backbone = load_weight(backbone, model_name='elannet_pico')
-        elif cfg['width'] == 0.25 and cfg['depth'] == 0.34:
+        if cfg['width'] == 0.25 and cfg['depth'] == 0.34:
             backbone = load_weight(backbone, model_name='elannet_nano')
         elif cfg['width'] == 0.375 and cfg['depth'] == 0.34:
             backbone = load_weight(backbone, model_name='elannet_tiny')