keep training YOLOvx-S

config/model_config/yolovx_config.py

@@ -40,7 +40,7 @@ yolovx_cfg = {
         'reg_max': 16,
         # ---------------- Train config ----------------
         ## Input
-        'multi_scale': [0.5, 1.5],   # 320 -> 960
+        'multi_scale': [0.5, 1.25],   # 320 -> 800
         'trans_type': 'yolovx_nano',
         # ---------------- Assignment config ----------------
         ## Matcher
@@ -94,7 +94,7 @@ yolovx_cfg = {
         'reg_max': 16,
         # ---------------- Train config ----------------
         ## Input
-        'multi_scale': [0.5, 1.5],   # 320 -> 960
+        'multi_scale': [0.5, 1.25],   # 320 -> 800
         'trans_type': 'yolovx_nano',
         # ---------------- Assignment config ----------------
         ## Matcher
@@ -148,7 +148,7 @@ yolovx_cfg = {
         'reg_max': 16,
         # ---------------- Train config ----------------
         ## Input
-        'multi_scale': [0.5, 1.5],   # 320 -> 960
+        'multi_scale': [0.5, 1.25],   # 320 -> 800
         'trans_type': 'yolovx_small',
         # ---------------- Assignment config ----------------
         ## Matcher
@@ -202,7 +202,7 @@ yolovx_cfg = {
         'reg_max': 16,
         # ---------------- Train config ----------------
         ## Input
-        'multi_scale': [0.5, 1.5],   # 320 -> 960
+        'multi_scale': [0.5, 1.25],   # 320 -> 800
         'trans_type': 'yolovx_medium',
         # ---------------- Assignment config ----------------
         ## Matcher

models/detectors/yolov3/yolov3_backbone.py

@@ -9,7 +9,7 @@ except:
 
 model_urls = {
     "darknet_tiny": "https://github.com/yjh0410/image_classification_pytorch/releases/download/weight/darknet_tiny.pth",
-    "darknet53": "https://github.com/yjh0410/image_classification_pytorch/releases/download/weight/darknet53_silu.pth",
+    "darknet53": None,
 }
 
 
@@ -148,7 +148,7 @@ def build_backbone(model_name='darknet53', pretrained=False):
 if __name__ == '__main__':
     import time
     from thop import profile
-    model, feats = build_backbone(model_name='darknet_tiny', pretrained=True)
+    model, feats = build_backbone(model_name='darknet53', pretrained=True)
     x = torch.randn(1, 3, 224, 224)
     t0 = time.time()
     outputs = model(x)

train_ddp.sh

@@ -16,4 +16,4 @@ python -m torch.distributed.run --nproc_per_node=8 train.py \
                                                     --fp16 \
                                                     --sybn \
                                                     --multi_scale \
-                                                    # --resume weights/coco/yolovx_s/yolovx_s_best.pth \
+                                                    --resume weights/coco/yolovx_s/yolovx_s_best.pth \