From a1151c04a735e90605dbbacc4b30113c646cef66 Mon Sep 17 00:00:00 2001
From: Glenn Jocher <glenn.jocher@ultralytics.com>
Date: Sun, 17 Nov 2019 18:48:50 -0800
Subject: [PATCH] updates

---
 train.py     | 21 ++++++++--------
 utils/gcp.sh | 71 +++++-----------------------------------------------
 2 files changed, 16 insertions(+), 76 deletions(-)

diff --git a/train.py b/train.py
index c96969fb..832ce0c2 100644
--- a/train.py
+++ b/train.py
@@ -104,8 +104,6 @@ def train():
     attempt_download(weights)
     if weights.endswith('.pt'):  # pytorch format
         # possible weights are '*.pt', 'yolov3-spp.pt', 'yolov3-tiny.pt' etc.
-        if opt.bucket:
-            os.system('gsutil cp gs://%s/last.pt %s' % (opt.bucket, last))  # download from bucket
         chkpt = torch.load(weights, map_location=device)
 
         # load model
@@ -347,8 +345,6 @@ def train():
 
             # Save last checkpoint
             torch.save(chkpt, last)
-            if opt.bucket and not opt.prebias:
-                os.system('gsutil cp %s gs://%s' % (last, opt.bucket))  # upload to bucket
 
             # Save best checkpoint
             if best_fitness == fitness:
@@ -365,18 +361,21 @@ def train():
 
     # end training
     if len(opt.name) and not opt.prebias:
-        os.rename('results.txt', 'results_%s.txt' % opt.name)
-        os.rename(wdir + 'last.pt', wdir + 'last_%s.pt' % opt.name) if os.path.exists(wdir + 'last.pt') else None
-        os.rename(wdir + 'best.pt', wdir + 'best_%s.pt' % opt.name) if os.path.exists(wdir + 'best.pt') else None
+        fresults, flast, fbest = 'results%s.txt' % opt.name, 'last%s.pt' % opt.name, 'best%s.pt' % opt.name
+        os.rename('results.txt', fresults)
+        os.rename(wdir + 'last.pt', wdir + flast) if os.path.exists(wdir + 'last.pt') else None
+        os.rename(wdir + 'best.pt', wdir + fbest) if os.path.exists(wdir + 'best.pt') else None
+
+        # save to cloud
+        if opt.bucket:
+            os.system('gsutil cp %s gs://%s' % (fresults, opt.bucket))
+            os.system('gsutil cp %s gs://%s' % (wdir + flast, opt.bucket))
+
     plot_results()  # save as results.png
     print('%g epochs completed in %.3f hours.\n' % (epoch - start_epoch + 1, (time.time() - t0) / 3600))
     dist.destroy_process_group() if torch.cuda.device_count() > 1 else None
     torch.cuda.empty_cache()
 
-    # save to cloud
-    # os.system('gsutil cp results.txt gs://...')
-    # os.system('gsutil cp weights/best.pt gs://...')
-
     return results
 
 
diff --git a/utils/gcp.sh b/utils/gcp.sh
index 2fef2b35..028ab47b 100755
--- a/utils/gcp.sh
+++ b/utils/gcp.sh
@@ -87,32 +87,6 @@ rm -rf darknet && git clone https://github.com/AlexeyAB/darknet && cd darknet &&
 ./darknet detector train ../supermarket2/supermarket2.data ../yolo_v3_spp_pan_scale.cfg darknet53.conv.74 -map -dont_show # train spp
 ./darknet detector train ../yolov3/data/coco.data ../yolov3-spp.cfg darknet53.conv.74 -map -dont_show # train spp coco
 
-./darknet detector train data/coco.data ../yolov3-spp.cfg darknet53.conv.74 -map -dont_show # train spp
-gsutil cp -r backup/*5000.weights gs://sm6/weights
-sudo shutdown
-
-
-./darknet detector train ../supermarket2/supermarket2.data ../yolov3-tiny-sm2-1cls.cfg yolov3-tiny.conv.15 -map -dont_show # train tiny
-./darknet detector train ../supermarket2/supermarket2.data cfg/yolov3-spp-sm2-1cls.cfg backup/yolov3-spp-sm2-1cls_last.weights  # resume
-python3 train.py --data ../supermarket2/supermarket2.data --cfg ../yolov3-spp-sm2-1cls.cfg --epochs 100 --num-workers 8 --img-size 320 --nosave  # train ultralytics
-python3 test.py --data ../supermarket2/supermarket2.data --weights ../darknet/backup/yolov3-spp-sm2-1cls_5000.weights --cfg cfg/yolov3-spp-sm2-1cls.cfg  # test
-gsutil cp -r backup/*.weights gs://sm6/weights  # weights to bucket
-
-python3 test.py --data ../supermarket2/supermarket2.data --weights weights/yolov3-spp-sm2-1cls_5000.weights --cfg ../yolov3-spp-sm2-1cls.cfg --img-size 320 --conf-thres 0.2  # test
-python3 test.py --data ../supermarket2/supermarket2.data --weights weights/yolov3-spp-sm2-1cls-scalexy_125_5000.weights --cfg ../yolov3-spp-sm2-1cls-scalexy_125.cfg --img-size 320 --conf-thres 0.2  # test
-python3 test.py --data ../supermarket2/supermarket2.data --weights weights/yolov3-spp-sm2-1cls-scalexy_150_5000.weights --cfg ../yolov3-spp-sm2-1cls-scalexy_150.cfg --img-size 320 --conf-thres 0.2  # test
-python3 test.py --data ../supermarket2/supermarket2.data --weights weights/yolov3-spp-sm2-1cls-scalexy_200_5000.weights --cfg ../yolov3-spp-sm2-1cls-scalexy_200.cfg --img-size 320 --conf-thres 0.2  # test
-python3 test.py --data ../supermarket2/supermarket2.data --weights ../darknet/backup/yolov3-spp-sm2-1cls-scalexy_variable_5000.weights --cfg ../yolov3-spp-sm2-1cls-scalexy_variable.cfg --img-size 320 --conf-thres 0.2  # test
-
-python3 train.py --img-size 320 --epochs 27 --batch-size 64 --accumulate 1 --nosave --notest && python3 test.py --weights weights/last.pt --img-size 320 --save-json && sudo shutdown
-
-# Debug/Development
-python3 train.py --data data/coco.data --img-size 320 --single-scale --batch-size 64 --accumulate 1 --epochs 1 --evolve --giou
-python3 test.py --weights weights/last.pt --cfg cfg/yolov3-spp.cfg --img-size 320
-
-gsutil cp evolve.txt gs://ultralytics
-sudo shutdown
-
 #Docker
 sudo docker kill $(sudo docker ps -q)
 sudo docker pull ultralytics/yolov3:v0
@@ -124,49 +98,16 @@ do
   python3 train.py --weights '' --prebias --img-size 512 --batch-size 32 --accumulate 2 --evolve --epochs 27 --bucket yolov4/512_coco_27e --device 0
 done
 
-python3 train.py --weights '' --prebias --img-size 512 --batch-size 16 --accumulate 4 --epochs 27 --device 0
+
+export tag=ultralytics/yolov3:v1 && sudo docker pull $tag && sudo nvidia-docker run -it --ipc=host --mount type=bind,source="$(pwd)"/coco,target=/usr/src/coco $tag python3 train.py --weights '' --epochs 27 --batch-size 32 --accumulate 2 --prebias --bucket yolov4 --name 63 --device 0
+export tag=ultralytics/yolov3:v2 && sudo docker pull $tag && sudo nvidia-docker run -it --ipc=host --mount type=bind,source="$(pwd)"/coco,target=/usr/src/coco $tag python3 train.py --weights '' --epochs 27 --batch-size 32 --accumulate 2 --prebias --bucket yolov4 --name 64 --device 1
+
+
+
 while true; do python3 train.py --data data/coco.data --img-size 320 --batch-size 64 --accumulate 1 --evolve --epochs 1 --adam --bucket yolov4/adamdefaultpw_coco_1e; done
 
 
 
-rm -rf yolov3  # Warning: remove existing
-git clone https://github.com/ultralytics/yolov3 && cd yolov3 # master
-python3 train.py --img-size 320 --data ../data/sm3/out.data --weights weights/yolov3-spp.weights --cfg cfg/yolov3-spp.cfg --prebias --epochs 300 --batch-size 32 --accumulate 2 --multi --name sm3b_yolov3_spp
-python3 train.py --img-size 320 --data ../data/sm3/out.data --weights weights/yolov3-tiny.weights --cfg cfg/yolov3-tiny.cfg --prebias --epochs 300 --batch-size 32 --accumulate 2 --multi --name sm3b_yolov3_tiny
-sudo shutdown
-
-
-rm -rf yolov3  # Warning: remove existing
-git clone https://github.com/ultralytics/yolov3 && cd yolov3 # master
-python3 train.py --data data/coco_64img.data --batch-size 16 --accumulate 1 --nosave --weights weights/yolov3-spp.weights --transfer --name yolov3-spp_transfer
-python3 train.py --data data/coco_64img.data --batch-size 16 --accumulate 1 --nosave --name from_scratch
-python3 train.py --data data/coco_64img.data --batch-size 16 --accumulate 1 --nosave --weights weights/darknet53.conv.74 --name darknet53_backbone
-python3 train.py --data data/coco_64img.data --batch-size 16 --accumulate 1 --nosave --weights weights/yolov3-spp.weights --name yolov3-spp_backbone
-sudo shutdown
-
-
-rm -rf yolov3  # Warning: remove existing
-git clone https://github.com/ultralytics/yolov3 && cd yolov3  # clone
-# bash yolov3/data/get_coco_dataset_gdrive.sh  # copy COCO2014 dataset (20GB)
-python3 train.py --data data/coco_1cls.data --batch-size 5 --accumulate 1 --weights weights/darknet53.conv.74 --nosave --cfg cfg/yolov3-spp.cfg --name 1cls
-python3 train.py --data data/coco_1cls.data --batch-size 5 --accumulate 1 --weights weights/darknet53.conv.74 --nosave --cfg cfg/yolov3-spp-1cls.cfg --name 1cls_1clscfg
-python3 -c "from utils import utils; utils.plot_results()"  # plot as 'results.png'
-
-
-clear
-python3 test.py --img-size 320 --save-json --weights weights/last.pt
-python3 test.py --img-size 416 --save-json --weights weights/last.pt
-python3 test.py --img-size 608 --save-json --weights weights/last.pt
-python3 test.py --img-size 640 --save-json --weights weights/last.pt --batch-size 8
-python3 test.py --img-size 800 --save-json --weights weights/last.pt --batch-size 8
-sudo shutdown
-
-
-clear
-rm -rf yolov3  # Warning: remove existing
-git clone https://github.com/ultralytics/yolov3 && cd yolov3  # clone
-python3 train.py --weights '' --img-size 512 --batch-size 32 --accumulate 2 --epochs 27 --prebias --nosave --notest --name 512default
-sudo shutdown