<details>
<summary>Table Notes (click to expand)</summary>
* AP<sup>test</sup> denotes COCO [test-dev2017](http://cocodataset.org/#upload) server results, all other AP results denote val2017 accuracy.
* AP values are for single-model single-scale unless otherwise noted. **Reproduce mAP** by `python test.py --data coco.yaml --img 640 --conf 0.001 --iou 0.65`
* Speed<sub>GPU</sub> averaged over 5000 COCO val2017 images using a GCP [n1-standard-16](https://cloud.google.com/compute/docs/machine-types#n1_standard_machine_types) V100 instance, and includes FP16 inference, postprocessing and NMS. **Reproduce speed** by `python test.py --data coco.yaml --img 640 --conf 0.25 --iou 0.45`
* All checkpoints are trained to 300 epochs with default settings and hyperparameters (no autoaugmentation).
* Test Time Augmentation ([TTA](https://github.com/ultralytics/yolov5/issues/303)) includes reflection and scale augmentation. **Reproduce TTA** by `python test.py --data coco.yaml --img 1536 --iou 0.7 --augment`
</details>
Changelog
Changes between **previous release and this release**: https://github.com/ultralytics/yolov5/compare/v4.0...v5.0
Changes **since this release**: https://github.com/ultralytics/yolov5/compare/v5.0...HEAD
**Click a section** below to **expand details**:
<details>
<summary>Implemented Enhancements (26) </summary>
- Return predictions as json [\2703](https://github.com/ultralytics/yolov5/issues/2703)
- Single channel image training？ [\2609](https://github.com/ultralytics/yolov5/issues/2609)
- Images in MPO Format are considered corrupted [\2446](https://github.com/ultralytics/yolov5/issues/2446)
- Improve Validation Visualization [\2384](https://github.com/ultralytics/yolov5/issues/2384)
- Add ASFF \(three fuse feature layers\) int the Head for V5\(s,m,l,x\) [\2348](https://github.com/ultralytics/yolov5/issues/2348)
- Dear author, can you provide a visualization scheme for YOLOV5 feature graphs during detect.py? Thank you! [\2259](https://github.com/ultralytics/yolov5/issues/2259)
- Dataloader [\2201](https://github.com/ultralytics/yolov5/issues/2201)
- Update Train Custom Data wiki page [\2187](https://github.com/ultralytics/yolov5/issues/2187)
- Multi-class NMS [\2162](https://github.com/ultralytics/yolov5/issues/2162)
- 💡Idea: Mosaic cropping using segmentation labels [\2151](https://github.com/ultralytics/yolov5/issues/2151)
- Improving Confusion Matrix Interpretability: FP and FN vectors should be switched to align with Predicted and True axis [\2071](https://github.com/ultralytics/yolov5/issues/2071)
- Interpreting model YoloV5 by Grad-cam [\2065](https://github.com/ultralytics/yolov5/issues/2065)
- Output optimal confidence threshold based on PR curve [\2048](https://github.com/ultralytics/yolov5/issues/2048)
- is it valuable that add --cache-images option to detect.py? [\2004](https://github.com/ultralytics/yolov5/issues/2004)
- I want to change the anchor box to anchor circles, where do you think the change to be made ? [\1987](https://github.com/ultralytics/yolov5/issues/1987)
- Support for imgaug [\1954](https://github.com/ultralytics/yolov5/issues/1954)
- Any plan for Knowledge Distillation? [\1762](https://github.com/ultralytics/yolov5/issues/1762)
- Is there a wasy to run detections on a video/webcam/rtrsp, etc EVERY x SECONDS? [\1742](https://github.com/ultralytics/yolov5/issues/1742)
- Can yolov5 support rotated target detection? [\1728](https://github.com/ultralytics/yolov5/issues/1728)
- Deploying yolov5 to TorchServe \(GPU compatible\) [\1681](https://github.com/ultralytics/yolov5/issues/1681)
- Why diffrent colors of bboxs? [\1638](https://github.com/ultralytics/yolov5/issues/1638)
- Yet another export yolov5 models to ONNX and inference with TensorRT [\1597](https://github.com/ultralytics/yolov5/issues/1597)
- Rerange the blocks of Focus Layer into `row major` to be compatible with tensorflow `SpaceToDepth` [\413](https://github.com/ultralytics/yolov5/issues/413)
- YouTube Livestream Detection [\2752](https://github.com/ultralytics/yolov5/pull/2752) ([ben-milanko](https://github.com/ben-milanko))
- Add TransformerLayer, TransformerBlock, C3TR modules [\2333](https://github.com/ultralytics/yolov5/pull/2333) ([dingyiwei](https://github.com/dingyiwei))
- Improved W&B integration [\2125](https://github.com/ultralytics/yolov5/pull/2125) ([AyushExel](https://github.com/AyushExel))
</details>
<details>
<summary>Fixed Bugs (73)</summary>
- it seems that check\_wandb\_resume don't support multiple input files of images. [\2716](https://github.com/ultralytics/yolov5/issues/2716)
- ip camera or web camera. error: \(-215:Assertion failed\) !ss ize.empty\(\) in function 'cv::resize' [\2709](https://github.com/ultralytics/yolov5/issues/2709)
- Model predict with forward will fail if PIL image does not have filename attribute [\2702](https://github.com/ultralytics/yolov5/issues/2702)
- ❔Question Whenever i try to run my model i run into this error AttributeError: 'NoneType' object has no attribute 'startswith' from wandbutils.py line 161 I wonder why ? Any workaround or fix [\2697](https://github.com/ultralytics/yolov5/issues/2697)
- coremltools no longer included in docker container [\2686](https://github.com/ultralytics/yolov5/issues/2686)
- 'LoadImages' path handling appears to be broken [\2618](https://github.com/ultralytics/yolov5/issues/2618)
- CUDA memory leak [\2586](https://github.com/ultralytics/yolov5/issues/2586)
- UnboundLocalError: local variable 'wandb\_logger' referenced before assignment [\2562](https://github.com/ultralytics/yolov5/issues/2562)
- RuntimeError: CUDA error: CUBLAS\_STATUS\_INTERNAL\_ERROR when calling `cublasCreate\(handle\)` [\2417](https://github.com/ultralytics/yolov5/issues/2417)
- CUDNN Mapping Error [\2415](https://github.com/ultralytics/yolov5/issues/2415)
- Can't train in DDP mode after recent update [\2405](https://github.com/ultralytics/yolov5/issues/2405)
- a bug about function bbox\_iou\(\) [\2376](https://github.com/ultralytics/yolov5/issues/2376)
- Training got stuck when I used DistributedDataParallel mode but dataParallel mode is useful [\2375](https://github.com/ultralytics/yolov5/issues/2375)
- Something wrong with fixing ema [\2343](https://github.com/ultralytics/yolov5/issues/2343)
- Conversion to CoreML fails when running with --batch 2 [\2322](https://github.com/ultralytics/yolov5/issues/2322)
- The "fitness" function in train.py. [\2303](https://github.com/ultralytics/yolov5/issues/2303)
- Error "Directory already existed" happen when training with multiple GPUs [\2275](https://github.com/ultralytics/yolov5/issues/2275)
- self.balance = {3: \[4.0, 1.0, 0.4\], 4: \[4.0, 1.0, 0.25, 0.06\], 5: \[4.0, 1.0, 0.25, 0.06, .02\]}\[det.nl\] [\2255](https://github.com/ultralytics/yolov5/issues/2255)
- Cannot run model with URL as argument [\2246](https://github.com/ultralytics/yolov5/issues/2246)
- Yolov5 crashes with RTSP stream analysis [\2226](https://github.com/ultralytics/yolov5/issues/2226)
- interruption during evolve [\2218](https://github.com/ultralytics/yolov5/issues/2218)
- I am a student of Tsinghua University, doing research in Tencent. When I train with yolov5, the following problems appear，Sincerely hope to get help, [\2203](https://github.com/ultralytics/yolov5/issues/2203)
- Frame Loss in video stream [\2196](https://github.com/ultralytics/yolov5/issues/2196)
- wandb.ai not logging epochs vs metrics/losses instead uses step [\2175](https://github.com/ultralytics/yolov5/issues/2175)
- Evolve is leaking files [\2142](https://github.com/ultralytics/yolov5/issues/2142)
- Issue in torchscript model inference [\2129](https://github.com/ultralytics/yolov5/issues/2129)
- RuntimeError: CUDA error: device-side assert triggered [\2124](https://github.com/ultralytics/yolov5/issues/2124)
- In 'evolve' mode, If the original hyp is 0, It will never update [\2122](https://github.com/ultralytics/yolov5/issues/2122)
- Caching image path [\2121](https://github.com/ultralytics/yolov5/issues/2121)
- can't convert cuda:0 device type tensor to numpy. Use Tensor.cpu\(\) to copy the tensor to host memory first [\2106](https://github.com/ultralytics/yolov5/issues/2106)
- Error in creating model with Ghost modules [\2081](https://github.com/ultralytics/yolov5/issues/2081)
- TypeError: int\(\) can't convert non-string with explicit base [\2066](https://github.com/ultralytics/yolov5/issues/2066)
- \[Pytorch Hub\] Hub CI is broken with latest master of yolo5 example. [\2050](https://github.com/ultralytics/yolov5/issues/2050)
- Problems when downloading requirements [\2047](https://github.com/ultralytics/yolov5/issues/2047)
- detect.py - images always saved [\2029](https://github.com/ultralytics/yolov5/issues/2029)
- thop and pycocotools shouldn't be hard requirements to train a model [\2014](https://github.com/ultralytics/yolov5/issues/2014)
- CoreML export failure [\2007](https://github.com/ultralytics/yolov5/issues/2007)
- loss function like has a bug [\1988](https://github.com/ultralytics/yolov5/issues/1988)
- CoreML export failure: unexpected number of inputs for node x.2 \(\_convolution\): 13 [\1945](https://github.com/ultralytics/yolov5/issues/1945)
- torch.nn.modules.module.ModuleAttributeError: 'Hardswish' object has no attribute 'inplace' [\1939](https://github.com/ultralytics/yolov5/issues/1939)
- runs not logging separately in wandb.ai [\1937](https://github.com/ultralytics/yolov5/issues/1937)
- wrong batch size after --resume on multiple GPUs [\1936](https://github.com/ultralytics/yolov5/issues/1936)
- TypeError: int\(\) can't convert non-string with explicit base [\1927](https://github.com/ultralytics/yolov5/issues/1927)
- RuntimeError: DataLoader worker [\1908](https://github.com/ultralytics/yolov5/issues/1908)
- Unable to export weights into onnx [\1900](https://github.com/ultralytics/yolov5/issues/1900)
- CUDA Initialization Warning on Docker when not passing in gpu [\1891](https://github.com/ultralytics/yolov5/issues/1891)
- Issue with github api rate limiting [\1890](https://github.com/ultralytics/yolov5/issues/1890)
- wandb: ERROR Error while calling W&B API: Error 1062: Duplicate entry '189160-gbp6y2en' for key 'PRIMARY' \(\<Response \[409\]\>\) [\1878](https://github.com/ultralytics/yolov5/issues/1878)
- Broken pipe [\1859](https://github.com/ultralytics/yolov5/issues/1859)
- detection.py [\1858](https://github.com/ultralytics/yolov5/issues/1858)
- Getting error on loading custom trained model [\1856](https://github.com/ultralytics/yolov5/issues/1856)
- W&B id is always the same and continue with the old logging. [\1851](https://github.com/ultralytics/yolov5/issues/1851)
- pytorch1.7 is not completely support.'inplace'! 'inplace'! 'inplace'! [\1832](https://github.com/ultralytics/yolov5/issues/1832)
- Validation errors are NaN [\1804](https://github.com/ultralytics/yolov5/issues/1804)
- Error Loading custom model weights with pytorch.hub.load [\1788](https://github.com/ultralytics/yolov5/issues/1788)
- 'cap' object is not self. initialized [\1781](https://github.com/ultralytics/yolov5/issues/1781)
- ValueError: API key must be 40 characters long, yours was 1 [\1777](https://github.com/ultralytics/yolov5/issues/1777)
- scipy [\1766](https://github.com/ultralytics/yolov5/issues/1766)
- error of missing key 'anchors' in hyp.scratch.yaml [\1744](https://github.com/ultralytics/yolov5/issues/1744)
- mss grab color conversion problem using TorchHub [\1735](https://github.com/ultralytics/yolov5/issues/1735)
- Video rotation when running detection. [\1725](https://github.com/ultralytics/yolov5/issues/1725)
- RuntimeError: CUDA out of memory. Tried to allocate 294.00 MiB \(GPU 0; 6.00 GiB total capacity; 118.62 MiB already allocated; 4.20 GiB free; 362.00 MiB reserved in total by PyTorch\) [\1698](https://github.com/ultralytics/yolov5/issues/1698)
- Errors on MAC [\1690](https://github.com/ultralytics/yolov5/issues/1690)
- RuntimeError: DataLoader worker \(pid\(s\) 296430\) exited unexpectedly [\1675](https://github.com/ultralytics/yolov5/issues/1675)
- Non-positive Stride [\1671](https://github.com/ultralytics/yolov5/issues/1671)
- gbk error. How can I solve it? [\1669](https://github.com/ultralytics/yolov5/issues/1669)
- CoreML export failure: unexpected number of inputs for node x.2 \(\_convolution\): 13 [\1667](https://github.com/ultralytics/yolov5/issues/1667)
- RuntimeError: Given groups=1, weight of size \[32, 128, 1, 1\], expected input\[1, 64, 32, 32\] to have 128 channels, but got 64 channels instead [\1627](https://github.com/ultralytics/yolov5/issues/1627)
- segmentation fault [\1620](https://github.com/ultralytics/yolov5/issues/1620)
- Getting different output sizes when using exported torchscript [\1562](https://github.com/ultralytics/yolov5/issues/1562)
- some bugs when training [\1547](https://github.com/ultralytics/yolov5/issues/1547)
- Evolve getting error [\1319](https://github.com/ultralytics/yolov5/issues/1319)
- AssertionError: Image Not Found ../dataset/images/train/4501.jpeg [\195](https://github.com/ultralytics/yolov5/issues/195)
</details>
<details>
<summary>Closed Issues (42)</summary>
- Can feed tensor the model [\2722](https://github.com/ultralytics/yolov5/issues/2722)
- hello, everyone, In order to modify the network more conveniently based on this rep., I restructure the network part, which is divided into backbone, neck, head [\2710](https://github.com/ultralytics/yolov5/issues/2710)
- Differentiate between normal banner and LED banner [\2647](https://github.com/ultralytics/yolov5/issues/2647)
- 👋 Hello Wilson-inclaims, thank you for your interest in 🚀 YOLOv5! Please visit our ⭐️ \[Tutorials\]\(https://github.com/ultralytics/yolov5/wiki\#tutorials\) to get started, where you can find quickstart guides for simple tasks like \[Custom Data Training\]\(https://github.com/ultralytics/yolov5/wiki/Train-Custom-Data\) all the way to advanced concepts like \[Hyperparameter Evolution\]\(https://github.com/ultralytics/yolov5/issues/607\). [\#2516](https://github.com/ultralytics/yolov5/issues/2516)
- I got a runtimerror when I run classifier.py to train my own dataset. [\2438](https://github.com/ultralytics/yolov5/issues/2438)
- RuntimeError: a view of a leaf Variable that requires grad is being used in an in-place operation. [\2403](https://github.com/ultralytics/yolov5/issues/2403)
- 🌟💡 YOLOv5 Study: batch size [\2377](https://github.com/ultralytics/yolov5/issues/2377)
- export.py export onnx for gpu failed [\2365](https://github.com/ultralytics/yolov5/issues/2365)
- in \_ddp\_init\_helper expect\_sparse\_gradient\) RuntimeError: Model replicas must have an equal number of parameters. [\2311](https://github.com/ultralytics/yolov5/issues/2311)
- Custom dataset training using YOLOv5 [\2296](https://github.com/ultralytics/yolov5/issues/2296)
- label format [\2293](https://github.com/ultralytics/yolov5/issues/2293)
- MAP NOT PRINTING [\2283](https://github.com/ultralytics/yolov5/issues/2283)
- Why didn't I get results in my video test? [\2277](https://github.com/ultralytics/yolov5/issues/2277)
- Label Missing: for images and labels... 203 found, 50 missing, 0 empty, 0 corrupted: 100% [\2268](https://github.com/ultralytics/yolov5/issues/2268)
- Pytorch Hub inference returns different results than detect.py [\2224](https://github.com/ultralytics/yolov5/issues/2224)
- yolov5x train.py error [\2181](https://github.com/ultralytics/yolov5/issues/2181)
- degrees is radians? [\2160](https://github.com/ultralytics/yolov5/issues/2160)
- AssertionError: Image Not Found [\2130](https://github.com/ultralytics/yolov5/issues/2130)
- How to load custom trained model to detect sample image? [\2097](https://github.com/ultralytics/yolov5/issues/2097)
- YOLOv5 installed failed on Macbook M1 [\2075](https://github.com/ultralytics/yolov5/issues/2075)
- How to set the number of seconds to detect once [\2072](https://github.com/ultralytics/yolov5/issues/2072)
- Where the changes should be made to detect horizontal line and vertical lines? Can anyone discus elaborately? [\2070](https://github.com/ultralytics/yolov5/issues/2070)
- Video inference stops after a certain number of frames [\2064](https://github.com/ultralytics/yolov5/issues/2064)
- Can't YOLOV5 be detected with multithreading? [\1979](https://github.com/ultralytics/yolov5/issues/1979)
- I want to make a images file what divided images in test.py [\1931](https://github.com/ultralytics/yolov5/issues/1931)
- different image size w/ torchscript windows c++ [\1920](https://github.com/ultralytics/yolov5/issues/1920)
- run detect the result ，the Image don't have box [\1910](https://github.com/ultralytics/yolov5/issues/1910)
- resume problem [\1884](https://github.com/ultralytics/yolov5/issues/1884)
- Detect source as .txt error [\1877](https://github.com/ultralytics/yolov5/issues/1877)
- yolov5 v4.0 tensorrt deployment [\1874](https://github.com/ultralytics/yolov5/issues/1874)
- Hyperparameter Evolution: load dataset every time [\1864](https://github.com/ultralytics/yolov5/issues/1864)
- Caching images problem [\1862](https://github.com/ultralytics/yolov5/issues/1862)
- About Release v4.0 [\1841](https://github.com/ultralytics/yolov5/issues/1841)
- glenn best practices for running trained YOLOv5 models in new python environments is to use PyTorch Hub. See PyTorch Hub Tutorial: [\1789](https://github.com/ultralytics/yolov5/issues/1789)
- yolov5x.pt is not compatible with ./models/yolov5x.yam [\1721](https://github.com/ultralytics/yolov5/issues/1721)
- Parameter '--device' doesn't work! [\1706](https://github.com/ultralytics/yolov5/issues/1706)
- Thank you for your issue! [\1687](https://github.com/ultralytics/yolov5/issues/1687)
- Convert the label format [\1652](https://github.com/ultralytics/yolov5/issues/1652)
- Autorun not working [\1599](https://github.com/ultralytics/yolov5/issues/1599)
- When model.model\[-1\]. export = False in export.py, coreml export failing. Please check. [\1491](https://github.com/ultralytics/yolov5/issues/1491)
- Error 'AttributeError: 'str' object has no attribute 'get'' at running train.py [\1479](https://github.com/ultralytics/yolov5/issues/1479)
- Docker image is not working, torch.nn.modules.module.ModuleAttributeError: 'Hardswish' object has no attribute 'inplace' [\1327](https://github.com/ultralytics/yolov5/issues/1327)
</details>
<details>
<summary>Merged Pull Requests (172)</summary>
- Tensorboard model visualization bug fix [\2758](https://github.com/ultralytics/yolov5/pull/2758) ([glenn-jocher](https://github.com/glenn-jocher))
- utils/wandb\_logging PEP8 reformat [\2755](https://github.com/ultralytics/yolov5/pull/2755) ([glenn-jocher](https://github.com/glenn-jocher))
- torch.cuda.amp bug fix [\2750](https://github.com/ultralytics/yolov5/pull/2750) ([glenn-jocher](https://github.com/glenn-jocher))
- autocast enable=torch.cuda.is\_available\(\) [\2748](https://github.com/ultralytics/yolov5/pull/2748) ([glenn-jocher](https://github.com/glenn-jocher))
- Add Hub results.pandas\(\) method [\2725](https://github.com/ultralytics/yolov5/pull/2725) ([glenn-jocher](https://github.com/glenn-jocher))
- Update README with collapsable notes [\2721](https://github.com/ultralytics/yolov5/pull/2721) ([glenn-jocher](https://github.com/glenn-jocher))
- Fix \2716: Add support for list-of-directory data format for wandb [\2719](https://github.com/ultralytics/yolov5/pull/2719) ([AyushExel](https://github.com/AyushExel))
- Updated filename attributes for YOLOv5 Hub BytesIO [\2718](https://github.com/ultralytics/yolov5/pull/2718) ([glenn-jocher](https://github.com/glenn-jocher))
- Updated filename attributes for YOLOv5 Hub results [\2708](https://github.com/ultralytics/yolov5/pull/2708) ([glenn-jocher](https://github.com/glenn-jocher))
- pip install coremltools onnx [\2690](https://github.com/ultralytics/yolov5/pull/2690) ([glenn-jocher](https://github.com/glenn-jocher))
- autoShape forward im = np.asarray\(im\) \ to numpy [\2689](https://github.com/ultralytics/yolov5/pull/2689) ([glenn-jocher](https://github.com/glenn-jocher))
- PyTorch Hub model.save\(\) increment as runs/hub/exp [\2684](https://github.com/ultralytics/yolov5/pull/2684) ([glenn-jocher](https://github.com/glenn-jocher))
- Fix: \2674 [\2683](https://github.com/ultralytics/yolov5/pull/2683) ([AyushExel](https://github.com/AyushExel))
- Update README with Tips for Best Results tutorial [\2682](https://github.com/ultralytics/yolov5/pull/2682) ([glenn-jocher](https://github.com/glenn-jocher))
- Disallow resume for dataset uploading [\2657](https://github.com/ultralytics/yolov5/pull/2657) ([AyushExel](https://github.com/AyushExel))
- Speed profiling improvements [\2648](https://github.com/ultralytics/yolov5/pull/2648) ([glenn-jocher](https://github.com/glenn-jocher))
- Add tqdm pbar.close\(\) [\2644](https://github.com/ultralytics/yolov5/pull/2644) ([zzttqu](https://github.com/zzttqu))
- PyTorch Hub amp.autocast\(\) inference [\2641](https://github.com/ultralytics/yolov5/pull/2641) ([glenn-jocher](https://github.com/glenn-jocher))
- PyTorch Hub custom model to CUDA device fix [\2636](https://github.com/ultralytics/yolov5/pull/2636) ([glenn-jocher](https://github.com/glenn-jocher))
- Improve git\_describe\(\) fix 1 [\2635](https://github.com/ultralytics/yolov5/pull/2635) ([glenn-jocher](https://github.com/glenn-jocher))
- Fix: evolve with wandb [\2634](https://github.com/ultralytics/yolov5/pull/2634) ([AyushExel](https://github.com/AyushExel))
- Improve git\_describe\(\) [\2633](https://github.com/ultralytics/yolov5/pull/2633) ([glenn-jocher](https://github.com/glenn-jocher))
- FROM nvcr.io/nvidia/pytorch:21.03-py3 [\2623](https://github.com/ultralytics/yolov5/pull/2623) ([glenn-jocher](https://github.com/glenn-jocher))
- Remove conflicting nvidia-tensorboard package [\2622](https://github.com/ultralytics/yolov5/pull/2622) ([glenn-jocher](https://github.com/glenn-jocher))
- Update Detections\(\) self.n comment [\2620](https://github.com/ultralytics/yolov5/pull/2620) ([glenn-jocher](https://github.com/glenn-jocher))
- Update detections\(\) self.t = tuple\(\) [\2617](https://github.com/ultralytics/yolov5/pull/2617) ([glenn-jocher](https://github.com/glenn-jocher))
- Create date\_modified\(\) [\2616](https://github.com/ultralytics/yolov5/pull/2616) ([glenn-jocher](https://github.com/glenn-jocher))
- Added '.mpo' to supported image formats [\2615](https://github.com/ultralytics/yolov5/pull/2615) ([maxupp](https://github.com/maxupp))
- Fix Indentation in test.py [\2614](https://github.com/ultralytics/yolov5/pull/2614) ([AyushExel](https://github.com/AyushExel))
- Update git\_describe\(\) for remote dir usage [\2606](https://github.com/ultralytics/yolov5/pull/2606) ([glenn-jocher](https://github.com/glenn-jocher))
- Remove Cython from requirements.txt [\2604](https://github.com/ultralytics/yolov5/pull/2604) ([glenn-jocher](https://github.com/glenn-jocher))
- resume.py fix DDP typo [\2603](https://github.com/ultralytics/yolov5/pull/2603) ([glenn-jocher](https://github.com/glenn-jocher))
- Update segment2box\(\) comment [\2600](https://github.com/ultralytics/yolov5/pull/2600) ([glenn-jocher](https://github.com/glenn-jocher))
- Save webcam results, add --nosave option [\2598](https://github.com/ultralytics/yolov5/pull/2598) ([glenn-jocher](https://github.com/glenn-jocher))
- YOLOv5 PyTorch Hub models \>\> check\_requirements\(\) [\2592](https://github.com/ultralytics/yolov5/pull/2592) ([glenn-jocher](https://github.com/glenn-jocher))
- YOLOv5 PyTorch Hub models \>\> check\_requirements\(\) [\2591](https://github.com/ultralytics/yolov5/pull/2591) ([glenn-jocher](https://github.com/glenn-jocher))
- YOLOv5 PyTorch Hub models \>\> check\_requirements\(\) [\2588](https://github.com/ultralytics/yolov5/pull/2588) ([glenn-jocher](https://github.com/glenn-jocher))
- W&B DDP fix 2 [\2587](https://github.com/ultralytics/yolov5/pull/2587) ([glenn-jocher](https://github.com/glenn-jocher))
- W&B resume ddp from run link fix [\2579](https://github.com/ultralytics/yolov5/pull/2579) ([AyushExel](https://github.com/AyushExel))
- YOLOv5 PyTorch Hub models \>\> check\_requirements\(\) [\2577](https://github.com/ultralytics/yolov5/pull/2577) ([glenn-jocher](https://github.com/glenn-jocher))
- Update tensorboard\>=2.4.1 [\2576](https://github.com/ultralytics/yolov5/pull/2576) ([glenn-jocher](https://github.com/glenn-jocher))
- Enhanced check\_requirements\(\) with auto-install [\2575](https://github.com/ultralytics/yolov5/pull/2575) ([glenn-jocher](https://github.com/glenn-jocher))
- W&B DDP fix [\2574](https://github.com/ultralytics/yolov5/pull/2574) ([AyushExel](https://github.com/AyushExel))
- check\_requirements\(\) exclude pycocotools, thop [\2571](https://github.com/ultralytics/yolov5/pull/2571) ([glenn-jocher](https://github.com/glenn-jocher))
- Update Detections\(\) times=None [\2570](https://github.com/ultralytics/yolov5/pull/2570) ([glenn-jocher](https://github.com/glenn-jocher))
- Add opencv-contrib-python to requirements.txt [\2564](https://github.com/ultralytics/yolov5/pull/2564) ([youngjinshin](https://github.com/youngjinshin))
- Supervisely Ecosystem [\2519](https://github.com/ultralytics/yolov5/pull/2519) ([mkolomeychenko](https://github.com/mkolomeychenko))
- add option to disable half precision when testing [\2507](https://github.com/ultralytics/yolov5/pull/2507) ([bfineran](https://github.com/bfineran))
- PyTorch Hub models default to CUDA:0 if available [\2472](https://github.com/ultralytics/yolov5/pull/2472) ([glenn-jocher](https://github.com/glenn-jocher))
- Scipy kmeans-robust autoanchor update [\2470](https://github.com/ultralytics/yolov5/pull/2470) ([glenn-jocher](https://github.com/glenn-jocher))
- Be able to create dataset from annotated images only [\2466](https://github.com/ultralytics/yolov5/pull/2466) ([kinoute](https://github.com/kinoute))
- autoShape\(\) speed profiling update [\2460](https://github.com/ultralytics/yolov5/pull/2460) ([glenn-jocher](https://github.com/glenn-jocher))
- Add autoShape\(\) speed profiling [\2459](https://github.com/ultralytics/yolov5/pull/2459) ([glenn-jocher](https://github.com/glenn-jocher))
- CVPR 2021 Argoverse-HD autodownload curl [\2455](https://github.com/ultralytics/yolov5/pull/2455) ([glenn-jocher](https://github.com/glenn-jocher))
- labels.jpg class names [\2454](https://github.com/ultralytics/yolov5/pull/2454) ([glenn-jocher](https://github.com/glenn-jocher))
- Update test.py --task train val study [\2453](https://github.com/ultralytics/yolov5/pull/2453) ([glenn-jocher](https://github.com/glenn-jocher))
- Integer printout [\2450](https://github.com/ultralytics/yolov5/pull/2450) ([glenn-jocher](https://github.com/glenn-jocher))
- DDP after autoanchor reorder [\2421](https://github.com/ultralytics/yolov5/pull/2421) ([glenn-jocher](https://github.com/glenn-jocher))
- CVPR 2021 Argoverse-HD autodownload fix [\2418](https://github.com/ultralytics/yolov5/pull/2418) ([glenn-jocher](https://github.com/glenn-jocher))
- CVPR 2021 Argoverse-HD dataset autodownload support [\2400](https://github.com/ultralytics/yolov5/pull/2400) ([karthiksharma98](https://github.com/karthiksharma98))
- GCP sudo docker userdata.sh [\2393](https://github.com/ultralytics/yolov5/pull/2393) ([glenn-jocher](https://github.com/glenn-jocher))
- AWS wait && echo "All tasks done." [\2391](https://github.com/ultralytics/yolov5/pull/2391) ([glenn-jocher](https://github.com/glenn-jocher))
- bbox\_iou\(\) stability and speed improvements [\2385](https://github.com/ultralytics/yolov5/pull/2385) ([glenn-jocher](https://github.com/glenn-jocher))
- image weights compatible faster random index generator v2 for mosaic … [\2383](https://github.com/ultralytics/yolov5/pull/2383) ([developer0hye](https://github.com/developer0hye))
- ENV HOME=/usr/src/app [\2382](https://github.com/ultralytics/yolov5/pull/2382) ([glenn-jocher](https://github.com/glenn-jocher))
- --no-cache notebook [\2381](https://github.com/ultralytics/yolov5/pull/2381) ([glenn-jocher](https://github.com/glenn-jocher))
- Resume with custom anchors fix [\2361](https://github.com/ultralytics/yolov5/pull/2361) ([glenn-jocher](https://github.com/glenn-jocher))
- Anchor override for training from scratch [\2350](https://github.com/ultralytics/yolov5/pull/2350) ([glenn-jocher](https://github.com/glenn-jocher))
- faster random index generator for mosaic augmentation [\2345](https://github.com/ultralytics/yolov5/pull/2345) ([developer0hye](https://github.com/developer0hye))
- Add --label-smoothing eps argument to train.py \(default 0.0\) [\2344](https://github.com/ultralytics/yolov5/pull/2344) ([ptran1203](https://github.com/ptran1203))
- FROM nvcr.io/nvidia/pytorch:21.02-py3 [\2341](https://github.com/ultralytics/yolov5/pull/2341) ([glenn-jocher](https://github.com/glenn-jocher))
- EMA bug fix 2 [\2330](https://github.com/ultralytics/yolov5/pull/2330) ([glenn-jocher](https://github.com/glenn-jocher))
- remove TTA 1 pixel offset [\2325](https://github.com/ultralytics/yolov5/pull/2325) ([glenn-jocher](https://github.com/glenn-jocher))
- Update Dockerfile install htop [\2320](https://github.com/ultralytics/yolov5/pull/2320) ([glenn-jocher](https://github.com/glenn-jocher))
- Update test.py [\2319](https://github.com/ultralytics/yolov5/pull/2319) ([glenn-jocher](https://github.com/glenn-jocher))
- final\_epoch EMA bug fix [\2317](https://github.com/ultralytics/yolov5/pull/2317) ([glenn-jocher](https://github.com/glenn-jocher))
- Fix labels being missed when image extension appears twice in filename [\2300](https://github.com/ultralytics/yolov5/pull/2300) ([idenc](https://github.com/idenc))
- W&B entity support [\2298](https://github.com/ultralytics/yolov5/pull/2298) ([toretak](https://github.com/toretak))
- GPU export options [\2297](https://github.com/ultralytics/yolov5/pull/2297) ([toretak](https://github.com/toretak))
- Improved model+EMA checkpointing fix [\2295](https://github.com/ultralytics/yolov5/pull/2295) ([glenn-jocher](https://github.com/glenn-jocher))
- Improved model+EMA checkpointing [\2292](https://github.com/ultralytics/yolov5/pull/2292) ([glenn-jocher](https://github.com/glenn-jocher))
- Update train.py [\2290](https://github.com/ultralytics/yolov5/pull/2290) ([glenn-jocher](https://github.com/glenn-jocher))
- Amazon AWS EC2 startup and re-startup scripts patch [\2282](https://github.com/ultralytics/yolov5/pull/2282) ([glenn-jocher](https://github.com/glenn-jocher))
- FLOPS min stride 32 [\2276](https://github.com/ultralytics/yolov5/pull/2276) ([xiaowo1996](https://github.com/xiaowo1996))
- Update Dockerfile with apt install zip [\2274](https://github.com/ultralytics/yolov5/pull/2274) ([glenn-jocher](https://github.com/glenn-jocher))
- Update greetings.yml for auto-rebase on PR [\2272](https://github.com/ultralytics/yolov5/pull/2272) ([glenn-jocher](https://github.com/glenn-jocher))
- Update minimum stride to 32 [\2266](https://github.com/ultralytics/yolov5/pull/2266) ([glenn-jocher](https://github.com/glenn-jocher))
- Robust objectness loss balancing [\2256](https://github.com/ultralytics/yolov5/pull/2256) ([glenn-jocher](https://github.com/glenn-jocher))
- Update inference default to multi\_label=False [\2252](https://github.com/ultralytics/yolov5/pull/2252) ([glenn-jocher](https://github.com/glenn-jocher))
- Improved hubconf.py CI tests [\2251](https://github.com/ultralytics/yolov5/pull/2251) ([glenn-jocher](https://github.com/glenn-jocher))
- YOLOv5 Hub URL inference bug fix [\2250](https://github.com/ultralytics/yolov5/pull/2250) ([glenn-jocher](https://github.com/glenn-jocher))
- Unified hub and detect.py box and labels plotting [\2243](https://github.com/ultralytics/yolov5/pull/2243) ([kinoute](https://github.com/kinoute))
- Add isdocker\(\) [\2232](https://github.com/ultralytics/yolov5/pull/2232) ([glenn-jocher](https://github.com/glenn-jocher))
- Add check\_imshow\(\) [\2231](https://github.com/ultralytics/yolov5/pull/2231) ([glenn-jocher](https://github.com/glenn-jocher))
- Update CI badge [\2230](https://github.com/ultralytics/yolov5/pull/2230) ([glenn-jocher](https://github.com/glenn-jocher))
- Update yolo.py channel array [\2223](https://github.com/ultralytics/yolov5/pull/2223) ([glenn-jocher](https://github.com/glenn-jocher))
- LoadStreams\(\) frame loss bug fix [\2222](https://github.com/ultralytics/yolov5/pull/2222) ([glenn-jocher](https://github.com/glenn-jocher))
- TTA augument boxes one pixel shifted in de-flip ud and lr [\2219](https://github.com/ultralytics/yolov5/pull/2219) ([VdLMV](https://github.com/VdLMV))
- Dynamic ONNX engine generation [\2208](https://github.com/ultralytics/yolov5/pull/2208) ([aditya-dl](https://github.com/aditya-dl))
- YOLOv5 PyTorch Hub results.save\(\) method retains filenames [\2194](https://github.com/ultralytics/yolov5/pull/2194) ([dan0nchik](https://github.com/dan0nchik))
- YOLOv5 Segmentation Dataloader Updates [\2188](https://github.com/ultralytics/yolov5/pull/2188) ([glenn-jocher](https://github.com/glenn-jocher))
- Amazon AWS EC2 startup and re-startup scripts [\2185](https://github.com/ultralytics/yolov5/pull/2185) ([glenn-jocher](https://github.com/glenn-jocher))
- PyTorch Hub results.save\('path/to/dir'\) [\2179](https://github.com/ultralytics/yolov5/pull/2179) ([glenn-jocher](https://github.com/glenn-jocher))
- Changed socket port and added timeout [\2176](https://github.com/ultralytics/yolov5/pull/2176) ([NanoCode012](https://github.com/NanoCode012))
- Update utils/datasets.py to support .webp files [\2174](https://github.com/ultralytics/yolov5/pull/2174) ([Transigent](https://github.com/Transigent))
- Update requirements.txt [\2173](https://github.com/ultralytics/yolov5/pull/2173) ([glenn-jocher](https://github.com/glenn-jocher))
- Update detect.py [\2167](https://github.com/ultralytics/yolov5/pull/2167) ([ab-101](https://github.com/ab-101))
- Update data-autodownload background tasks [\2154](https://github.com/ultralytics/yolov5/pull/2154) ([glenn-jocher](https://github.com/glenn-jocher))
- Linear LR scheduler option [\2150](https://github.com/ultralytics/yolov5/pull/2150) ([glenn-jocher](https://github.com/glenn-jocher))
- Update train.py batch\_size \* 2 [\2149](https://github.com/ultralytics/yolov5/pull/2149) ([glenn-jocher](https://github.com/glenn-jocher))
- Update train.py test batch\_size [\2148](https://github.com/ultralytics/yolov5/pull/2148) ([glenn-jocher](https://github.com/glenn-jocher))
- LoadImages\(\) pathlib update [\2140](https://github.com/ultralytics/yolov5/pull/2140) ([glenn-jocher](https://github.com/glenn-jocher))
- Unique \*.cache filenames fix [\2134](https://github.com/ultralytics/yolov5/pull/2134) ([train255](https://github.com/train255))
- Making inference thread-safe by avoiding mutable state in Detect class [\2120](https://github.com/ultralytics/yolov5/pull/2120) ([olehb](https://github.com/olehb))
- Make normalized confusion matrix more interpretable [\2114](https://github.com/ultralytics/yolov5/pull/2114) ([rbavery](https://github.com/rbavery))
- Update plot\_study\(\) [\2112](https://github.com/ultralytics/yolov5/pull/2112) ([glenn-jocher](https://github.com/glenn-jocher))
- Update test.py --task speed and study [\2099](https://github.com/ultralytics/yolov5/pull/2099) ([glenn-jocher](https://github.com/glenn-jocher))
- Add variable-stride inference support [\2091](https://github.com/ultralytics/yolov5/pull/2091) ([glenn-jocher](https://github.com/glenn-jocher))
- Add Kaggle badge [\2090](https://github.com/ultralytics/yolov5/pull/2090) ([glenn-jocher](https://github.com/glenn-jocher))
- Add Amazon Deep Learning AMI environment [\2085](https://github.com/ultralytics/yolov5/pull/2085) ([glenn-jocher](https://github.com/glenn-jocher))
- Add YOLOv5-P6 models [\2083](https://github.com/ultralytics/yolov5/pull/2083) ([glenn-jocher](https://github.com/glenn-jocher))
- GhostConv update [\2082](https://github.com/ultralytics/yolov5/pull/2082) ([glenn-jocher](https://github.com/glenn-jocher))
- W&B epoch logging update [\2073](https://github.com/ultralytics/yolov5/pull/2073) ([glenn-jocher](https://github.com/glenn-jocher))
- Update to colors.TABLEAU\_COLORS [\2069](https://github.com/ultralytics/yolov5/pull/2069) ([glenn-jocher](https://github.com/glenn-jocher))
- Update run-once lines [\2058](https://github.com/ultralytics/yolov5/pull/2058) ([glenn-jocher](https://github.com/glenn-jocher))
- Metric-Confidence plots feature addition [\2057](https://github.com/ultralytics/yolov5/pull/2057) ([glenn-jocher](https://github.com/glenn-jocher))
- Add histogram equalization fcn [\2049](https://github.com/ultralytics/yolov5/pull/2049) ([glenn-jocher](https://github.com/glenn-jocher))
- Confusion matrix native image-space fix [\2046](https://github.com/ultralytics/yolov5/pull/2046) ([ramonhollands](https://github.com/ramonhollands))
- Check im.format during dataset caching [\2042](https://github.com/ultralytics/yolov5/pull/2042) ([glenn-jocher](https://github.com/glenn-jocher))
- Add exclude tuple to check\_requirements\(\) [\2041](https://github.com/ultralytics/yolov5/pull/2041) ([glenn-jocher](https://github.com/glenn-jocher))
- data-autodownload background tasks [\2034](https://github.com/ultralytics/yolov5/pull/2034) ([glenn-jocher](https://github.com/glenn-jocher))
- Docker pyYAML\>=5.3.1 fix [\2031](https://github.com/ultralytics/yolov5/pull/2031) ([glenn-jocher](https://github.com/glenn-jocher))
- PyYAML==5.4.1 [\2030](https://github.com/ultralytics/yolov5/pull/2030) ([glenn-jocher](https://github.com/glenn-jocher))
- Update autoshape .print\(\) and .save\(\) [\2022](https://github.com/ultralytics/yolov5/pull/2022) ([glenn-jocher](https://github.com/glenn-jocher))
- Update requirements.txt [\2021](https://github.com/ultralytics/yolov5/pull/2021) ([glenn-jocher](https://github.com/glenn-jocher))
- Update general.py check\_git\_status\(\) fix [\2020](https://github.com/ultralytics/yolov5/pull/2020) ([glenn-jocher](https://github.com/glenn-jocher))
- Update inference multiple-counting [\2019](https://github.com/ultralytics/yolov5/pull/2019) ([glenn-jocher](https://github.com/glenn-jocher))
- Update ci-testing.yml --img 128 [\2018](https://github.com/ultralytics/yolov5/pull/2018) ([glenn-jocher](https://github.com/glenn-jocher))
- Update google\_utils.py attempt\_download\(\) fix [\2017](https://github.com/ultralytics/yolov5/pull/2017) ([glenn-jocher](https://github.com/glenn-jocher))
- Update Dockerfile [\2016](https://github.com/ultralytics/yolov5/pull/2016) ([glenn-jocher](https://github.com/glenn-jocher))
- check\_git\_status\(\) Windows fix [\2015](https://github.com/ultralytics/yolov5/pull/2015) ([glenn-jocher](https://github.com/glenn-jocher))
- --verbose on final\_epoch [\1997](https://github.com/ultralytics/yolov5/pull/1997) ([glenn-jocher](https://github.com/glenn-jocher))
- Add xywhn2xyxy\(\) [\1983](https://github.com/ultralytics/yolov5/pull/1983) ([glenn-jocher](https://github.com/glenn-jocher))
- Update Dockerfile [\1982](https://github.com/ultralytics/yolov5/pull/1982) ([glenn-jocher](https://github.com/glenn-jocher))
- check\_git\_status\(\) asserts [\1977](https://github.com/ultralytics/yolov5/pull/1977) ([glenn-jocher](https://github.com/glenn-jocher))
- Update train.py [\1972](https://github.com/ultralytics/yolov5/pull/1972) ([Anon-Artist](https://github.com/Anon-Artist))
- Update autoanchor.py [\1971](https://github.com/ultralytics/yolov5/pull/1971) ([Anon-Artist](https://github.com/Anon-Artist))
- Update yolo.py [\1970](https://github.com/ultralytics/yolov5/pull/1970) ([Anon-Artist](https://github.com/Anon-Artist))
- Update test.py [\1969](https://github.com/ultralytics/yolov5/pull/1969) ([Anon-Artist](https://github.com/Anon-Artist))
- Update plots.py [\1968](https://github.com/ultralytics/yolov5/pull/1968) ([Anon-Artist](https://github.com/Anon-Artist))
- check\_git\_status\(\) when not exist /workspace [\1966](https://github.com/ultralytics/yolov5/pull/1966) ([glenn-jocher](https://github.com/glenn-jocher))
- Security Fix for Arbitrary Code Execution - huntr.dev [\1962](https://github.com/ultralytics/yolov5/pull/1962) ([huntr-helper](https://github.com/huntr-helper))
- prevent check\_git\_status\(\) in docker images [\1951](https://github.com/ultralytics/yolov5/pull/1951) ([glenn-jocher](https://github.com/glenn-jocher))
- Add ComputeLoss\(\) class [\1950](https://github.com/ultralytics/yolov5/pull/1950) ([glenn-jocher](https://github.com/glenn-jocher))
- W&B mosaic log bug fix [\1949](https://github.com/ultralytics/yolov5/pull/1949) ([glenn-jocher](https://github.com/glenn-jocher))
- Start setting up the improved W&B integration [\1948](https://github.com/ultralytics/yolov5/pull/1948) ([AyushExel](https://github.com/AyushExel))
- W&B log epoch [\1946](https://github.com/ultralytics/yolov5/pull/1946) ([glenn-jocher](https://github.com/glenn-jocher))
- Daemon thread mosaic plots fix [\1943](https://github.com/ultralytics/yolov5/pull/1943) ([glenn-jocher](https://github.com/glenn-jocher))
- Fix batch-size on resume for multi-gpu [\1942](https://github.com/ultralytics/yolov5/pull/1942) ([NanoCode012](https://github.com/NanoCode012))
- Add nn.SiLU inplace in attempt\_load\(\) [\1940](https://github.com/ultralytics/yolov5/pull/1940) ([1991wangliang](https://github.com/1991wangliang))
- GitHub API rate limit fallback [\1930](https://github.com/ultralytics/yolov5/pull/1930) ([glenn-jocher](https://github.com/glenn-jocher))
- check\_git\_status\(\) bug fix [\1925](https://github.com/ultralytics/yolov5/pull/1925) ([glenn-jocher](https://github.com/glenn-jocher))
- check\_git\_status\(\) improvements [\1916](https://github.com/ultralytics/yolov5/pull/1916) ([glenn-jocher](https://github.com/glenn-jocher))
- Colorstr\(\) updates [\1909](https://github.com/ultralytics/yolov5/pull/1909) ([glenn-jocher](https://github.com/glenn-jocher))
- PyTorch Hub results.render\(\) [\1897](https://github.com/ultralytics/yolov5/pull/1897) ([glenn-jocher](https://github.com/glenn-jocher))
- Docker CUDA warning fix [\1895](https://github.com/ultralytics/yolov5/pull/1895) ([glenn-jocher](https://github.com/glenn-jocher))
- GitHub API rate limit fix [\1894](https://github.com/ultralytics/yolov5/pull/1894) ([glenn-jocher](https://github.com/glenn-jocher))
- Add colorstr\(\) [\1887](https://github.com/ultralytics/yolov5/pull/1887) ([glenn-jocher](https://github.com/glenn-jocher))
- auto-verbose if nc \<= 20 [\1869](https://github.com/ultralytics/yolov5/pull/1869) ([glenn-jocher](https://github.com/glenn-jocher))
- actions/stalev3 [\1868](https://github.com/ultralytics/yolov5/pull/1868) ([glenn-jocher](https://github.com/glenn-jocher))
- Add check\_requirements\(\) [\1853](https://github.com/ultralytics/yolov5/pull/1853) ([glenn-jocher](https://github.com/glenn-jocher))
- W&B ID reset on training completion [\1852](https://github.com/ultralytics/yolov5/pull/1852) ([TommyZihao](https://github.com/TommyZihao))
</details>