Allow YOLOv5 execution from arbitrary `cwd` (#4954)

detect.py

@@ -19,6 +19,7 @@ FILE = Path(__file__).resolve()
 ROOT = FILE.parents[0]  # YOLOv5 root directory
 if str(ROOT) not in sys.path:
     sys.path.append(str(ROOT))  # add ROOT to PATH
+ROOT = ROOT.relative_to(Path.cwd())  # relative
 
 from models.experimental import attempt_load
 from utils.datasets import LoadImages, LoadStreams
@@ -30,8 +31,8 @@ from utils.torch_utils import load_classifier, select_device, time_sync
 
 
 @torch.no_grad()
-def run(weights='yolov5s.pt',  # model.pt path(s)
-        source='data/images',  # file/dir/URL/glob, 0 for webcam
+def run(weights=ROOT / 'yolov5s.pt',  # model.pt path(s)
+        source=ROOT / 'data/images',  # file/dir/URL/glob, 0 for webcam
         imgsz=640,  # inference size (pixels)
         conf_thres=0.25,  # confidence threshold
         iou_thres=0.45,  # NMS IOU threshold
@@ -47,7 +48,7 @@ def run(weights='yolov5s.pt',  # model.pt path(s)
         augment=False,  # augmented inference
         visualize=False,  # visualize features
         update=False,  # update all models
-        project='runs/detect',  # save results to project/name
+        project=ROOT / 'runs/detect',  # save results to project/name
         name='exp',  # save results to project/name
         exist_ok=False,  # existing project/name ok, do not increment
         line_thickness=3,  # bounding box thickness (pixels)
@@ -55,6 +56,7 @@ def run(weights='yolov5s.pt',  # model.pt path(s)
         hide_conf=False,  # hide confidences
         half=False,  # use FP16 half-precision inference
         ):
+    source = str(source)
     save_img = not nosave and not source.endswith('.txt')  # save inference images
     webcam = source.isnumeric() or source.endswith('.txt') or source.lower().startswith(
         ('rtsp://', 'rtmp://', 'http://', 'https://'))
@@ -254,8 +256,8 @@ def run(weights='yolov5s.pt',  # model.pt path(s)
 
 def parse_opt():
     parser = argparse.ArgumentParser()
-    parser.add_argument('--weights', nargs='+', type=str, default='yolov5s.pt', help='model path(s)')
-    parser.add_argument('--source', type=str, default='data/images', help='file/dir/URL/glob, 0 for webcam')
+    parser.add_argument('--weights', nargs='+', type=str, default=ROOT / 'yolov5s.pt', help='model path(s)')
+    parser.add_argument('--source', type=str, default=ROOT / 'data/images', help='file/dir/URL/glob, 0 for webcam')
     parser.add_argument('--imgsz', '--img', '--img-size', nargs='+', type=int, default=[640], help='inference size h,w')
     parser.add_argument('--conf-thres', type=float, default=0.25, help='confidence threshold')
     parser.add_argument('--iou-thres', type=float, default=0.45, help='NMS IoU threshold')
@@ -271,7 +273,7 @@ def parse_opt():
     parser.add_argument('--augment', action='store_true', help='augmented inference')
     parser.add_argument('--visualize', action='store_true', help='visualize features')
     parser.add_argument('--update', action='store_true', help='update all models')
-    parser.add_argument('--project', default='runs/detect', help='save results to project/name')
+    parser.add_argument('--project', default=ROOT / 'runs/detect', help='save results to project/name')
     parser.add_argument('--name', default='exp', help='save results to project/name')
     parser.add_argument('--exist-ok', action='store_true', help='existing project/name ok, do not increment')
     parser.add_argument('--line-thickness', default=3, type=int, help='bounding box thickness (pixels)')

export.py

@@ -34,6 +34,7 @@ FILE = Path(__file__).resolve()
 ROOT = FILE.parents[0]  # YOLOv5 root directory
 if str(ROOT) not in sys.path:
     sys.path.append(str(ROOT))  # add ROOT to PATH
+ROOT = ROOT.relative_to(Path.cwd())  # relative
 
 from models.common import Conv
 from models.experimental import attempt_load

train.py

@@ -30,6 +30,7 @@ FILE = Path(__file__).resolve()
 ROOT = FILE.parents[0]  # YOLOv5 root directory
 if str(ROOT) not in sys.path:
     sys.path.append(str(ROOT))  # add ROOT to PATH
+ROOT = ROOT.relative_to(Path.cwd())  # relative
 
 import val  # for end-of-epoch mAP
 from models.experimental import attempt_load
@@ -429,10 +430,10 @@ def train(hyp,  # path/to/hyp.yaml or hyp dictionary
 
 def parse_opt(known=False):
     parser = argparse.ArgumentParser()
-    parser.add_argument('--weights', type=str, default='yolov5s.pt', help='initial weights path')
+    parser.add_argument('--weights', type=str, default=ROOT / 'yolov5s.pt', help='initial weights path')
     parser.add_argument('--cfg', type=str, default='', help='model.yaml path')
-    parser.add_argument('--data', type=str, default='data/coco128.yaml', help='dataset.yaml path')
-    parser.add_argument('--hyp', type=str, default='data/hyps/hyp.scratch.yaml', help='hyperparameters path')
+    parser.add_argument('--data', type=str, default=ROOT / 'data/coco128.yaml', help='dataset.yaml path')
+    parser.add_argument('--hyp', type=str, default=ROOT / 'data/hyps/hyp.scratch.yaml', help='hyperparameters path')
     parser.add_argument('--epochs', type=int, default=300)
     parser.add_argument('--batch-size', type=int, default=16, help='total batch size for all GPUs')
     parser.add_argument('--imgsz', '--img', '--img-size', type=int, default=640, help='train, val image size (pixels)')
@@ -451,8 +452,8 @@ def parse_opt(known=False):
     parser.add_argument('--adam', action='store_true', help='use torch.optim.Adam() optimizer')
     parser.add_argument('--sync-bn', action='store_true', help='use SyncBatchNorm, only available in DDP mode')
     parser.add_argument('--workers', type=int, default=8, help='maximum number of dataloader workers')
-    parser.add_argument('--project', default='runs/train', help='save to project/name')
     parser.add_argument('--entity', default=None, help='W&B entity')
+    parser.add_argument('--project', default=ROOT / 'runs/train', help='save to project/name')
     parser.add_argument('--name', default='exp', help='save to project/name')
     parser.add_argument('--exist-ok', action='store_true', help='existing project/name ok, do not increment')
     parser.add_argument('--quad', action='store_true', help='quad dataloader')
@@ -486,10 +487,11 @@ def main(opt, callbacks=Callbacks()):
         opt.cfg, opt.weights, opt.resume = '', ckpt, True  # reinstate
         LOGGER.info(f'Resuming training from {ckpt}')
     else:
-        opt.data, opt.cfg, opt.hyp = check_file(opt.data), check_yaml(opt.cfg), check_yaml(opt.hyp)  # check YAMLs
+        opt.data, opt.cfg, opt.hyp, opt.weights, opt.project = \
+            check_file(opt.data), check_yaml(opt.cfg), check_yaml(opt.hyp), str(opt.weights), str(opt.project)  # checks
         assert len(opt.cfg) or len(opt.weights), 'either --cfg or --weights must be specified'
         if opt.evolve:
-            opt.project = 'runs/evolve'
+            opt.project = str(ROOT / 'runs/evolve')
             opt.exist_ok, opt.resume = opt.resume, False  # pass resume to exist_ok and disable resume
         opt.save_dir = str(increment_path(Path(opt.project) / opt.name, exist_ok=opt.exist_ok))
 

val.py

@@ -21,6 +21,7 @@ FILE = Path(__file__).resolve()
 ROOT = FILE.parents[0]  # YOLOv5 root directory
 if str(ROOT) not in sys.path:
     sys.path.append(str(ROOT))  # add ROOT to PATH
+ROOT = ROOT.relative_to(Path.cwd())  # relative
 
 from models.experimental import attempt_load
 from utils.datasets import create_dataloader
@@ -95,7 +96,7 @@ def run(data,
         save_hybrid=False,  # save label+prediction hybrid results to *.txt
         save_conf=False,  # save confidences in --save-txt labels
         save_json=False,  # save a COCO-JSON results file
-        project='runs/val',  # save to project/name
+        project=ROOT / 'runs/val',  # save to project/name
         name='exp',  # save to project/name
         exist_ok=False,  # existing project/name ok, do not increment
         half=True,  # use FP16 half-precision inference
@@ -297,8 +298,8 @@ def run(data,
 
 def parse_opt():
     parser = argparse.ArgumentParser()
-    parser.add_argument('--data', type=str, default='data/coco128.yaml', help='dataset.yaml path')
-    parser.add_argument('--weights', nargs='+', type=str, default='yolov5s.pt', help='model.pt path(s)')
+    parser.add_argument('--data', type=str, default=ROOT / 'data/coco128.yaml', help='dataset.yaml path')
+    parser.add_argument('--weights', nargs='+', type=str, default=ROOT / 'yolov5s.pt', help='model.pt path(s)')
     parser.add_argument('--batch-size', type=int, default=32, help='batch size')
     parser.add_argument('--imgsz', '--img', '--img-size', type=int, default=640, help='inference size (pixels)')
     parser.add_argument('--conf-thres', type=float, default=0.001, help='confidence threshold')
@@ -312,14 +313,14 @@ def parse_opt():
     parser.add_argument('--save-hybrid', action='store_true', help='save label+prediction hybrid results to *.txt')
     parser.add_argument('--save-conf', action='store_true', help='save confidences in --save-txt labels')
     parser.add_argument('--save-json', action='store_true', help='save a COCO-JSON results file')
-    parser.add_argument('--project', default='runs/val', help='save to project/name')
+    parser.add_argument('--project', default=ROOT / 'runs/val', help='save to project/name')
     parser.add_argument('--name', default='exp', help='save to project/name')
     parser.add_argument('--exist-ok', action='store_true', help='existing project/name ok, do not increment')
     parser.add_argument('--half', action='store_true', help='use FP16 half-precision inference')
     opt = parser.parse_args()
+    opt.data = check_yaml(opt.data)  # check YAML
     opt.save_json |= opt.data.endswith('coco.yaml')
     opt.save_txt |= opt.save_hybrid
-    opt.data = check_yaml(opt.data)  # check YAML
     print_args(FILE.stem, opt)
     return opt