remove check_requirements (#37)

* remove `check_requirements`

* update to v0.5.7

yolov5/__init__.py

@@ -1,4 +1,4 @@
 from yolov5.helpers import YOLOv5
 from yolov5.helpers import load_model as load
 
-__version__ = "5.0.6"
+__version__ = "5.0.7"

yolov5/detect.py

@@ -16,7 +16,7 @@
 
 from yolov5.models.experimental import attempt_load
 from yolov5.utils.datasets import LoadStreams, LoadImages
-from yolov5.utils.general import check_img_size, check_requirements, check_imshow, colorstr, non_max_suppression, \
+from yolov5.utils.general import check_img_size, check_imshow, colorstr, non_max_suppression, \
     apply_classifier, scale_coords, xyxy2xywh, strip_optimizer, set_logging, increment_path, save_one_box, yolov5_in_syspath
 from yolov5.utils.plots import colors, plot_one_box
 from yolov5.utils.torch_utils import select_device, load_classifier, time_synchronized
@@ -213,7 +213,7 @@ def parse_opt():
 def main():
     opt = parse_opt()
     print(colorstr('detect: ') + ', '.join(f'{k}={v}' for k, v in vars(opt).items()))
-    check_requirements(exclude=('tensorboard', 'thop'))
+    #check_requirements(exclude=('tensorboard', 'thop'))
     run(**vars(opt))
 
 

yolov5/export.py

@@ -17,7 +17,7 @@
 from yolov5.models.yolo import Detect
 from yolov5.models.experimental import attempt_load
 from yolov5.utils.activations import Hardswish, SiLU
-from yolov5.utils.general import colorstr, check_img_size, check_requirements, file_size, set_logging
+from yolov5.utils.general import colorstr, check_img_size, file_size, set_logging
 from yolov5.utils.torch_utils import select_device
 
 
@@ -106,7 +106,7 @@ def run(weights='./yolov5s.pt',  # weights path
             # Simplify
             if simplify:
                 try:
-                    check_requirements(['onnx-simplifier'])
+                    #check_requirements(['onnx-simplifier'])
                     import onnxsim
 
                     print(f'{prefix} simplifying with onnx-simplifier {onnxsim.__version__}...')

yolov5/hubconf.py

@@ -26,12 +26,12 @@ def _create(name, pretrained=True, channels=3, classes=80, autoshape=True, verbo
     from pathlib import Path
 
     from yolov5.models.yolo import Model, attempt_load
-    from yolov5.utils.general import check_requirements, set_logging, yolov5_in_syspath
+    from yolov5.utils.general import set_logging, yolov5_in_syspath
     from yolov5.utils.google_utils import attempt_download
     from yolov5.utils.torch_utils import select_device
 
-    check_requirements(requirements=Path(__file__).parent / 'requirements.txt',
-                       exclude=('tensorboard', 'thop', 'opencv-python'))
+    #check_requirements(requirements=Path(__file__).parent / 'requirements.txt',
+    #                   exclude=('tensorboard', 'thop', 'opencv-python'))
     set_logging(verbose=verbose)
 
     fname = Path(name).with_suffix('.pt')  # checkpoint filename

yolov5/test.py

@@ -19,7 +19,7 @@
 
 from yolov5.models.experimental import attempt_load
 from yolov5.utils.datasets import create_dataloader
-from yolov5.utils.general import coco80_to_coco91_class, check_dataset, check_file, check_img_size, check_requirements, \
+from yolov5.utils.general import coco80_to_coco91_class, check_dataset, check_file, check_img_size,  \
     box_iou, non_max_suppression, scale_coords, xyxy2xywh, xywh2xyxy, set_logging, increment_path, colorstr
 from yolov5.utils.metrics import ap_per_class, ConfusionMatrix
 from yolov5.utils.plots import plot_images, output_to_target, plot_study_txt
@@ -274,7 +274,7 @@ def run(data,
             json.dump(jdict, f)
 
         try:  # https://github.com/cocodataset/cocoapi/blob/master/PythonAPI/pycocoEvalDemo.ipynb
-            check_requirements(['pycocotools'])
+            #check_requirements(['pycocotools'])
             from pycocotools.coco import COCO
             from pycocotools.cocoeval import COCOeval
 
@@ -333,7 +333,7 @@ def main():
     opt = parse_opt()
     set_logging()
     print(colorstr('test: ') + ', '.join(f'{k}={v}' for k, v in vars(opt).items()))
-    check_requirements(exclude=('tensorboard', 'thop'))
+    #check_requirements(exclude=('tensorboard', 'thop'))
 
     if opt.task in ('train', 'val', 'test'):  # run normally
         run(**vars(opt))

yolov5/train.py

@@ -37,7 +37,7 @@
 from yolov5.utils.datasets import create_dataloader
 from yolov5.utils.general import labels_to_class_weights, increment_path, labels_to_image_weights, init_seeds, \
     fitness, strip_optimizer, get_latest_run, check_dataset, check_file, check_git_status, check_img_size, \
-    check_requirements, print_mutation, set_logging, one_cycle, colorstr, yolov5_in_syspath
+    print_mutation, set_logging, one_cycle, colorstr, yolov5_in_syspath
 from yolov5.utils.google_utils import attempt_download
 from yolov5.utils.loss import ComputeLoss
 from yolov5.utils.plots import plot_images, plot_labels, plot_results, plot_evolution
@@ -549,7 +549,7 @@ def main(opt):
     if RANK in [-1, 0]:
         print(colorstr('train: ') + ', '.join(f'{k}={v}' for k, v in vars(opt).items()))
         check_git_status()
-        check_requirements(exclude=['thop'])
+        #check_requirements(exclude=['thop'])
 
     # Resume
     wandb_run = check_wandb_resume(opt)

yolov5/utils/datasets.py

@@ -23,7 +23,7 @@
 from torch.utils.data import Dataset
 from tqdm import tqdm
 
-from yolov5.utils.general import check_requirements, check_file, check_dataset, xyxy2xywh, xywh2xyxy, xywhn2xyxy, xyn2xy, \
+from yolov5.utils.general import check_file, check_dataset, xyxy2xywh, xywh2xyxy, xywhn2xyxy, xyn2xy, \
     segment2box, segments2boxes, resample_segments, clean_str, yolov5_in_syspath
 from yolov5.utils.torch_utils import torch_distributed_zero_first
 
@@ -283,7 +283,7 @@ def __init__(self, sources='streams.txt', img_size=640, stride=32):
             # Start thread to read frames from video stream
             print(f'{i + 1}/{n}: {s}... ', end='')
             if 'youtube.com/' in s or 'youtu.be/' in s:  # if source is YouTube video
-                check_requirements(('pafy', 'youtube_dl'))
+                #check_requirements(('pafy', 'youtube_dl'))
                 import pafy
                 s = pafy.new(s).getbest(preftype="mp4").url  # YouTube URL
             s = eval(s) if s.isnumeric() else s  # i.e. s = '0' local webcam