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ultralytics 8.1.23
add YOLOv9-C and E models
#8571
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Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## main #8571 +/- ##
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- Coverage 78.94% 75.96% -2.98%
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Files 117 117
Lines 14709 14797 +88
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- Hits 11612 11241 -371
- Misses 3097 3556 +459
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ultralytics 8.1.21
add YOLOv9-C and E models
@Laughing-q nice work on this!!! |
@glenn-jocher do you think we should rename the model to Currently the links of pretrained weights in yolov9.md are broken, please let me know your thought before merging this PR so I can upload the weights. |
@Laughing-q please also add/provide a pre-trained Thank you very much for your work. |
@Laughing-q I think removing |
@codename-cn thank you for the feedback! We have started an internal discussion about these, and if we choose to include them, you will see an Issue get added to the YOLO Project so make sure to check back there for updates. It's a lot of work to integrate new models and we all have a lot of other planned work as well, so please be patient with us π Of course you're also welcome to open a PR to integrate the segmentation pretrained models as well. |
@Laughing-q yes, we should update the naming convention to match ours as you suggested. |
@Laughing-q ok I think this looks good. Once you rename the models can you upload the assets or are you lacking permissions in the assets repo? Oh I forgot, we need to add the models also the offline assets list here (to avoid overwhelming the GitHub API by only using it if the file is not in this list): ultralytics/ultralytics/utils/downloads.py Lines 19 to 30 in 1146bb0
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@glenn-jocher Done! Pretrained-weights are also uploaded |
ultralytics 8.1.21
add YOLOv9-C and E modelsultralytics 8.1.22
add YOLOv9-C and E models
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
@Laughing-q ok I think this is all set now. I just wanted to pass the yolov9 weights through the same script I used for the worldv2 weights to strip dill and add the new docs and license keys to the checkpoints dicts. I should be able to do that later today when I get up, or if you want you could try yourself also using the script I saved in the worldv2 PR. |
ultralytics 8.1.22
add YOLOv9-C and E modelsultralytics 8.1.23
add YOLOv9-C and E models
@glenn-jocher sure no problem, I could update the weights later |
@glenn-jocher Done! |
@Laughing-q awesome, tested and everything looks good. Merging PR! |
Hello, @Laughing-q! Will you upload code for Dual training mode? |
Amazing ππ |
@Ilyabasharov Hi, we think the model performs pretty good even without any aux branches while training(dual training mode), so currently supporting this is not in our schedule yet. :) But if you would like to implement this mode and open a PR, we're very welcome and will be there to review. :) Thanks! |
Thanks for adding yolov9 support, I create yolov9-*.yaml for supporting more tasks. This is my first time to use yolov8 codebase, if I have time to read and understand code, I will try to integrate dual training. |
@WongKinYiu hi there! π Thanks for contributing the yolov9-*.yaml files to support more tasks. Your initiative is greatly appreciated! If you decide to explore dual training integration later on, we'd be excited to see your contributions. Don't hesitate to reach out if you have any questions while navigating the yolov8 codebase. Happy coding! |
Does it work with a custom trained model? Cause when I run a custom train model, I get the error yolo predict model=yolov8n.pt |
@iconictg hi there! π Yes, YOLOv9 does work with custom trained models. The error you're encountering might be due to specifying the wrong model file in your command. Make sure to replace yolo predict model=path/to/your/custom_model.pt If your custom model file is named yolo predict model=runs/train/exp/best.pt Hope this helps! Let us know if you have any more questions. |
@iconictg also make sure you're updated from ultralytics import YOLO
model = YOLO("yolov9c.pt")
result = model.train(data="data.yaml", ...,) # use your training arguments here Once training is completed, you can load your custom trained model using the |
It the model I train galan-c and thought that would work and it doesn't Yolov9-c works. Unable to train that in colab cause its so large.
Thank you guys.
β¦________________________________
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Sent: Thursday, March 7, 2024 2:36 PM
To: ultralytics/ultralytics ***@***.***>
Cc: Timothy Goebel ***@***.***>; Mention ***@***.***>
Subject: Re: [ultralytics/ultralytics] `ultralytics 8.1.23` add YOLOv9-C and E models (PR #8571)
@iconictg<https://github.com/iconictg> also make sure you're updated ultralytics to at least 8.1.23 or higher. Then you'll need to use
from ultralytics import YOLO
model = YOLO("yolov9c.pt")
result = model.train(data="data.yaml", ...,) # use your training arguments here
Once training is completed, you can load your custom trained model using the YOLO class and perform inference. Be sure to visit the docs pages<https://docs.ultralytics.com/> to learn more!
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Reply to this email directly, view it on GitHub<#8571 (comment)>, or unsubscribe<https://github.com/notifications/unsubscribe-auth/BGQD36JUPF2KYTDANTAXUS3YXDFT5AVCNFSM6AAAAABEBF5SCOVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMYTSOBUGM3TSNRWGM>.
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@iconictg hey there! π It sounds like you're encountering some size constraints with training YOLOv9-C on Colab due to its large size. For training larger models like YOLOv9-C, you might consider using a more powerful environment or reducing the model size if possible. For YOLOv9-C, ensure you're using the correct model configuration and have enough resources allocated on Colab. Sometimes, adjusting batch sizes or using a simpler model variant can help fit within Colab's limitations. If YOLOv9-C is too large, you might explore training with YOLOv8 models or other YOLOv9 variants that require less memory. Here's a quick example of how to adjust the batch size for training: from ultralytics import YOLO
model = YOLO("yolov9c.pt")
result = model.train(data="data.yaml", batch_size=16) # Adjust batch_size as needed Remember, training large models on Colab can be challenging due to resource limits. Consider using local resources or cloud services with higher capacities for such tasks. Hope this helps, and happy coding! |
Hi Glenn,
I have trained YoloV8 with no issues at all. Yolov9-c was the only issues yes I have change the batch size too.
thank you,
Timothy Goebel
β¦________________________________
From: Glenn Jocher ***@***.***>
Sent: Friday, March 8, 2024 12:11 AM
To: ultralytics/ultralytics ***@***.***>
Cc: Timothy Goebel ***@***.***>; Mention ***@***.***>
Subject: Re: [ultralytics/ultralytics] `ultralytics 8.1.23` add YOLOv9-C and E models (PR #8571)
@iconictg<https://github.com/iconictg> hey there! π It sounds like you're encountering some size constraints with training YOLOv9-C on Colab due to its large size. For training larger models like YOLOv9-C, you might consider using a more powerful environment or reducing the model size if possible.
For YOLOv9-C, ensure you're using the correct model configuration and have enough resources allocated on Colab. Sometimes, adjusting batch sizes or using a simpler model variant can help fit within Colab's limitations.
If YOLOv9-C is too large, you might explore training with YOLOv8 models or other YOLOv9 variants that require less memory. Here's a quick example of how to adjust the batch size for training:
from ultralytics import YOLO
model = YOLO("yolov9c.pt")
result = model.train(data="data.yaml", batch_size=16) # Adjust batch_size as needed
Remember, training large models on Colab can be challenging due to resource limits. Consider using local resources or cloud services with higher capacities for such tasks. Hope this helps, and happy coding!
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Reply to this email directly, view it on GitHub<#8571 (comment)>, or unsubscribe<https://github.com/notifications/unsubscribe-auth/BGQD36PECVGZBEAV6BXHV4TYXFJAJAVCNFSM6AAAAABEBF5SCOVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMYTSOBVGA4TMOJZGI>.
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Great to hear you've had success with YOLOv8! π For YOLOv9-C, adjusting the batch size is a good move. If you're still facing issues, it might be worth trying to tweak other parameters like from ultralytics import YOLO
# Assuming 'yolov9c.yaml' is your model configuration file
model = YOLO('yolov9c.yaml')
model.train(data='data.yaml', batch_size=4, accumulate=4) # Adjust 'accumulate' as needed This approach allows you to effectively increase your batch size without increasing memory usage. If you're still running into obstacles, consider reaching out with specific error messages or behaviors you're observing. We're here to help! |
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<glenn.jocher@ultralytics.com> Co-authored-by: UltralyticsAssistant <web@ultralytics.com> Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Fix PIL `show()` and `save()` (ultralytics#8202) Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Remove OpenVINO INT8 RTDETRDecoder ops (ultralytics#8219) * Fix xyxyxyxyn calculation, swap axis (ultralytics#8249) * Improve Docs Modes tables (ultralytics#8266) Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * `ultralytics 8.1.15` add Python 3.12 compatibility (ultralytics#8210) Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Co-authored-by: Johnny <johnnynuca14@gmail.com> Co-authored-by: UltralyticsAssistant <web@ultralytics.com> * Expand `Model` method type hinting (ultralytics#8279) Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * `ultralytics 8.1.16` OBB ConfusionMatrix support (ultralytics#8299) Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Co-authored-by: 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add YOLOv8x-World support (ultralytics#8539) Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Fix device counting method to account for double-digit device IDs (ultralytics#8502) Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Remove unused variables (ultralytics#8511) Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Add NCNN Docs Integrations Page (ultralytics#8562) Co-authored-by: UltralyticsAssistant <web@ultralytics.com> Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Optimize function calls to method calls (ultralytics#8507) Co-authored-by: UltralyticsAssistant <web@ultralytics.com> Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Replacing Images for torchscript.md (ultralytics#8596) Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Fix cmake requirements for ARM64 (ultralytics#8589) Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Add https://youtu.be/rCggzXRRSRo to Speed Estimation Docs (ultralytics#8577) Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Add KaTeX support + updates to YOLOv9 model page (ultralytics#8531) Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Replace `onnx2tf` usage from CLI to Python (ultralytics#8429) Co-authored-by: UltralyticsAssistant <web@ultralytics.com> Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Update IoU capitalization (ultralytics#8604) Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Co-authored-by: Dean Mark <2552482+deanmark@users.noreply.github.com> * Update TFLite Docs images (ultralytics#8605) Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Add `distance calculation` feature in `vision-eye` (ultralytics#8616) Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Co-authored-by: Muhammad Rizwan Munawar <chr043416@gmail.com> Co-authored-by: UltralyticsAssistant <web@ultralytics.com> * `ultralytics 8.1.21` Add YOLOv8-World-v2 models (ultralytics#8580) Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> Co-authored-by: UltralyticsAssistant <web@ultralytics.com> * `ultralytics 8.1.22` HUB model `pathlib` fix (ultralytics#8621) Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * `ultralytics 8.1.23` add YOLOv9-C and E models (ultralytics#8571) Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Co-authored-by: UltralyticsAssistant <web@ultralytics.com> Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Add settings `runs_dir` == `datasets_dir` warning (ultralytics#8653) Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Add Ultralytics HUB Cloud Training banner to Docs (ultralytics#8656) Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Update CITATION.cff with cffinit corrections (ultralytics#8658) * Update Colab notebook for YOLOv8.1 (ultralytics#8660) * `ultralytics 8.1.24` new OpenVINO 2023.3 export updates (ultralytics#8417) Co-authored-by: UltralyticsAssistant <web@ultralytics.com> Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * OBB: Fix when training on zip data (ultralytics#8680) Co-authored-by: UltralyticsAssistant <web@ultralytics.com> Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Object Counter improvements (ultralytics#8648) Co-authored-by: UltralyticsAssistant <web@ultralytics.com> Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Clarify triton server boolean value (ultralytics#8532) Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Add `model.eval()` in TensorBoad graph visualization to avoid BN stats changes (ultralytics#8629) Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Add domain checks to CI docs page (ultralytics#8714) * `ultralytics 8.1.25` OpenVINO `LATENCY` and `THROUGHPUT` modes (ultralytics#8058) Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Co-authored-by: UltralyticsAssistant <web@ultralytics.com> Co-authored-by: Adrian Boguszewski <adekboguszewski@gmail.com> * Add https://youtu.be/OpWpBI35A5Y to inference-api Docs (ultralytics#8717) * OpenVino 2024.0.0 (ultralytics#8726) Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Fix tfjs exports for ARM64 Dockerfile (ultralytics#8766) Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Modify tuner best.pt logic to train first (ultralytics#8792) * Update CI.md with CI links (ultralytics#8786) * Add https://youtu.be/ZzUSXQkLbNw to Integration Docs (ultralytics#8793) Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * `ultralytics 8.1.25` fix `**kwargs: (dict)` warnings (ultralytics#8815) Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Add docs guide terminal images (ultralytics#8819) Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * `RTDETRDetectionModel` TorchScript, ONNX Predict and Val support (ultralytics#8818) Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * New `MLFLOW_KEEP_RUN_ACTIVE` flag for enhanced MLflow run management (ultralytics#8808) Co-authored-by: UltralyticsAssistant <web@ultralytics.com> Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * `ultralytics 8.1.26` `LoadImagesAndVideos` batched inference (ultralytics#8817) Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Update `fraction` arg to employ a random selection (ultralytics#8234) Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Batch inference fixes (ultralytics#8854) * Integrate OpenVINO `CUMULATIVE_THROUGHPUT` mode batched inference (ultralytics#8834) Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Add PaddlePaddle Docs Integrations Page (ultralytics#8858) Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * `ultralytics 8.1.27` batched tracking fixes (ultralytics#8842) Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Faster batch `same_shapes` (ultralytics#8851) * More robust PNNX downloads (ultralytics#8866) * Fix `test_mlflow_keep_run_active()` (ultralytics#8868) * Add polygon regions drawing support in `object-counting.md` and minor docs update (ultralytics#8885) * Add TFLite Edge TPU Docs Integrations Page (ultralytics#8900) Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Update Docs README (ultralytics#8919) * Fix `names` bug when exporting YOLOv8-World to ONNX (ultralytics#8941) Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * New test for labels and crops (ultralytics#8861) Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Optimize TFJS export on ARM64 (ultralytics#8946) Co-authored-by: UltralyticsAssistant <web@ultralytics.com> Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Auto-format by https://ultralytics.com/actions * `ultralytics 8.1.28` avoid * ops on bool Tensors for RT-DETR OpenVINO export (ultralytics#8937) Co-authored-by: UltralyticsAssistant <web@ultralytics.com> Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Add https://youtu.be/YDXKa1EljmU and https://youtu.be/5BO0Il_YYAg to Docs (ultralytics#8958) * `ultralytics 8.1.29` improved disk space checking on correct path (ultralytics#8977) Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Co-authored-by: Kayzwer <68285002+Kayzwer@users.noreply.github.com> * Add OpenVINO Latency vs Throughput modes Docs page (ultralytics#9001) Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Add `brain-tumor` dataset docs page (ultralytics#9041) Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Fix Neural Magic links (ultralytics#9144) * Updating a typo on paddlepaddle.md (ultralytics#9108) Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * `ultralytics 8.1.30` add advanced HUB train arguments (ultralytics#9110) Co-authored-by: UltralyticsAssistant <web@ultralytics.com> Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * fix yolo classify model loading error (ultralytics#9196) * Add TF GraphDef Docs Integrations Page (ultralytics#9203) Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * `ultralytics 8.1.31` NCNN and CLIP updates (ultralytics#9235) Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Fix TypeError in check_cfg() (ultralytics#9245) Co-authored-by: UltralyticsAssistant <web@ultralytics.com> Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Add https://youtu.be/aeAX6vWpfR0 to docs & `african-wildlife` dataset docs page (ultralytics#9102) Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Add TF SavedModel Docs Integrations Page (ultralytics#9162) Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Limit `ray<2.9.3` due to bug in `ray==2.10.0` (ultralytics#9254) Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * `ultralytics 8.1.32` fix CLIP backwards compatibility (ultralytics#9253) Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Conda cv2 ImportError libEGL.so.1 fix (ultralytics#9255) * Fix `IS_PYTHON_3_12` bug (ultralytics#9258) Co-authored-by: UltralyticsAssistant <web@ultralytics.com> * Reverse IoU threshold for NMS docs descriptions (ultralytics#9151) Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Add `bgr` hyperparameter (ultralytics#9139) Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Update pyproject.toml `[tool.pytest.ini_options]` (ultralytics#9259) Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Fix OpenVINO missing batch-size bug (ultralytics#9264) * `ultralytics 8.1.33` fix HUB model checks (ultralytics#9153) Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Co-authored-by: Laughing <61612323+Laughing-q@users.noreply.github.com> Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Update Discord and Contributing Guide URLs (ultralytics#9270) Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Add https://youtu.be/uDrn9QZJ2lk and `object_counting.py`, `ai_gym.py` updates (ultralytics#9265) * `ultralytics 8.1.34` Inference API robust imgsz checks (ultralytics#9274) Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Bump contributor-assistant/github-action from 2.3.1 to 2.3.2 in /.github/workflows (ultralytics#9279) Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> * Add https://youtu.be/u3pLlgzUeV8 to docs (ultralytics#9367) * Fix typo in YOLOv8-Libtorch-CPP-Inference (ultralytics#9330) Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Simplify metrics calculation (ultralytics#9338) Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Fix typo in example readme (ultralytics#9306) Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Specify YOLODataset task arg during INT8 calibration (ultralytics#9309) Co-authored-by: UltralyticsAssistant <web@ultralytics.com> Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * `ultralytics 8.1.35` simplify network modules (ultralytics#9321) Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> --------- Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Signed-off-by: dependabot[bot] <support@github.com> Signed-off-by: Skillnoob <78843978+Skillnoob@users.noreply.github.com> Co-authored-by: Muhammad Rizwan Munawar <chr043416@gmail.com> Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> Co-authored-by: UltralyticsAssistant <web@ultralytics.com> Co-authored-by: Ayush Chaurasia <ayush.chaurarsia@gmail.com> Co-authored-by: Abirami Vina <abirami.vina@gmail.com> Co-authored-by: Paula Derrenger <107626595+pderrenger@users.noreply.github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> Co-authored-by: Yonghye Kwon <developer.0hye@gmail.com> Co-authored-by: Muhammad Rizwan Munawar 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<32206511+Y-T-G@users.noreply.github.com> Co-authored-by: Finlay Morrison <57669260+finlaymorrison@users.noreply.github.com> Co-authored-by: Massimiliano Riva <48362794+massimiliano96@users.noreply.github.com> Co-authored-by: Jamjamjon <51357717+jamjamjon@users.noreply.github.com> Co-authored-by: Kalen Michael <kalenmike@gmail.com> Co-authored-by: Mo Li <82895469+DseidLi@users.noreply.github.com> Co-authored-by: zhaoruibing <zhaoruibing@gmail.com> Co-authored-by: Dzmitry Plashchynski <plashchynski@gmail.com> Co-authored-by: higor-melo <115033428+higor-melo@users.noreply.github.com> Co-authored-by: Eric Hanson <5846501+ericphanson@users.noreply.github.com> Co-authored-by: sifan-intel <109498696+sifan-intel@users.noreply.github.com>
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Co-authored-by: UltralyticsAssistant <web@ultralytics.com> Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Does yolov9c or yolov9e supports obb ? |
Hi there! π YOLOv9c and YOLOv9e currently do not natively support oriented bounding boxes (OBB). These models are optimized for regular bounding boxes. However, you can modify the model architecture or post-processing steps to integrate OBB functionality if needed. If you have specific requirements or further questions, feel free to ask! |
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Co-authored-by: UltralyticsAssistant <web@ultralytics.com> Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
π οΈ PR Summary
Made with β€οΈ by Ultralytics Actions
π Summary
Extended YOLOv9 documentation and model configurations, added new neural network modules, and updated the package version.
π Key Changes
RepNCSPELAN4
,ADown
,SPPELAN
,CBFuse
,CBLinear
, andSilence
.exporter.py
.__init__.py
from "8.1.22" to "8.1.23".block.py
to include documentation and definitions for the new neural network modules.π― Purpose & Impact