From c4a07275e83e5ed0f26b10ddd3929c4c2d9e3356 Mon Sep 17 00:00:00 2001
From: NASEEM A P <naseemalassampattil@gmail.com>
Date: Sun, 24 Sep 2023 10:35:58 +0530
Subject: [PATCH 1/3] fixed issue with resume - added train_params[resume] =
 True

---
 train.py | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/train.py b/train.py
index 896d093..bce2fe1 100644
--- a/train.py
+++ b/train.py
@@ -184,6 +184,10 @@
         "metric_to_watch": 'mAP@0.50'
     }
 
+    # to Resume Training
+    if args['resume']:
+        train_params['resume'] = True
+    
     trainer.train(
         model=model, 
         training_params=train_params, 

From e8c2f1aea4c629fdb64e49b802e434f827d827da Mon Sep 17 00:00:00 2001
From: NASEEM A P <naseemalassampattil@gmail.com>
Date: Sun, 24 Sep 2023 11:28:20 +0530
Subject: [PATCH 2/3] fixed issue with resume training, now it will resume from
 the last, eg:- (50/100) to (100/100)

---
 train.py | 28 ++++++++++++++++++----------
 1 file changed, 18 insertions(+), 10 deletions(-)

diff --git a/train.py b/train.py
index bce2fe1..27f43b0 100644
--- a/train.py
+++ b/train.py
@@ -60,20 +60,25 @@
 
     s_time = time.time()
 
+    
     if args['name'] is None:
         name = 'train'
     else:
         name = args['name']
-    n = 0
-    while True:
-        if not os.path.exists(os.path.join('runs', f'{name}{n}')):
-            name = f'{name}{n}'
-            os.makedirs(os.path.join('runs', name))
-            print(f"[INFO] Checkpoints saved in \033[1m{os.path.join('runs', name)}\033[0m")
-            break
-        else:
-            n += 1
-
+    
+    if args['resume']:
+        name = os.path.split(args['weight'])[0].split('/')[-1]
+    else:
+        n = 0
+        while True:
+            if not os.path.exists(os.path.join('runs', f'{name}{n}')):
+                name = f'{name}{n}'
+                os.makedirs(os.path.join('runs', name))
+                break
+            else:
+                n += 1
+                
+    print(f"[INFO] Checkpoints saved in \033[1m{os.path.join('runs', name)}\033[0m")
     # Training on GPU or CPU
     if args['cpu']:
         print('[INFO] Training on \033[1mCPU\033[0m')
@@ -188,6 +193,9 @@
     if args['resume']:
         train_params['resume'] = True
     
+    # Print Training Params
+    print('[INFO] Training Params:\n', train_params)
+
     trainer.train(
         model=model, 
         training_params=train_params, 

From 73c0e399a1b7fe31bafeb973e57ca30aa8b2a9d1 Mon Sep 17 00:00:00 2001
From: NASEEM A P <naseemalassampattil@gmail.com>
Date: Sun, 24 Sep 2023 11:33:57 +0530
Subject: [PATCH 3/3] added training resume to README

---
 README.md | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/README.md b/README.md
index 10c4638..8a014a1 100644
--- a/README.md
+++ b/README.md
@@ -134,6 +134,12 @@ You can train your **YOLO-NAS** model with **Single Command Line**
 ```
 python3 train.py --data /dir/dataset/data.yaml --batch 6 --epoch 100 --model yolo_nas_m --size 640
 ```
+### If your training ends in 65th epoch (total 100 epochs), now you can start from 65th epoch and complete your 100 epochs training.
+**Example:**
+```
+python3 train.py --data /dir/dataset/data.yaml --batch 6 --epoch 100 --model yolo_nas_m --size 640 \
+                 --weight runs/train2/ckpt_latest.pth --resume
+```
 
 ## 📺 Inference
 You can Inference your **YOLO-NAS** model with **Single Command Line**