train YOLOv7-Tiny on COCO

config/yolov7_config.py

@@ -4,7 +4,7 @@ yolov7_cfg = {
     'yolov7_nano':{
         # input
         'trans_type': 'yolov5_nano',
-        'multi_scale': [0.5, 1.5], # 320 -> 960
+        'multi_scale': [0.5, 1.25], # 320 -> 800
         # model
         'backbone': 'elannet_nano',
         'pretrained': True,
@@ -62,7 +62,7 @@ yolov7_cfg = {
     'yolov7_tiny':{
         # input
         'trans_type': 'yolov5_weak',
-        'multi_scale': [0.5, 1.5], # 320 -> 960
+        'multi_scale': [0.5, 1.25], # 320 -> 800
         # model
         'backbone': 'elannet_tiny',
         'pretrained': True,
@@ -120,7 +120,7 @@ yolov7_cfg = {
     'yolov7_large':{
         # input
         'trans_type': 'yolov5_strong',
-        'multi_scale': [0.5, 1.5], # 320 -> 960
+        'multi_scale': [0.5, 1.25], # 320 -> 800
         # model
         'backbone': 'elannet_large',
         'pretrained': True,
@@ -178,7 +178,7 @@ yolov7_cfg = {
     'yolov7_huge':{
         # input
         'trans_type': 'yolov5_strong',
-        'multi_scale': [0.5, 1.5], # 320 -> 960
+        'multi_scale': [0.5, 1.25], # 320 -> 800
         # model
         'backbone': 'elannet_huge',
         'pretrained': True,

train.py

@@ -197,7 +197,7 @@ def train():
     # start training loop
     best_map = -1.0
     last_opt_step = -1
-    total_epochs = args.max_epoch
+    total_epochs = args.max_epoch + args.wp_epoch
     heavy_eval = False
     optimizer.zero_grad()
     

train.sh

@@ -3,7 +3,7 @@ python train.py \
         --cuda \
         -d coco \
         --root /mnt/share/ssd2/dataset/ \
-        -m yolov7_large \
+        -m yolov7_tiny \
         -bs 16 \
         -size 640 \
         --wp_epoch 1 \