training_extensions
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Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO™
Hi, I encounter this error when I am running the fine-tuning step in [https://github.com/openvinotoolkit/training_extensions/tree/misc/models/object_detection/model_templates/horizontal-text-detection](url) Step 4.b. Evaluate Traceback (most recent call last): File "/home/tham/training_extensions/external/mmdetection/tools/test.py", line 260, in No CUDA runtime...
I trained an object detection model based on **YOLOX** with [otx](https://github.com/openvinotoolkit/training_extensions) and exported / optimized it as openvino model. The network includes a `NonMaxSuppression` operator to post-process the detected objects...
**Describe the bug** While running the OTX API following [this doc](https://openvinotoolkit.github.io/training_extensions/latest/guide/tutorials/advanced/api_tutorial.html#model-template-and-dataset-loading) , in executing below command, ```python dataset_adapter = get_dataset_adapter(task_type = model_template.task_type, # set a path to the root folder...
**Describe the bug** When training tilling ins-seg model with "coco decremental dataset" which is used for regression test dataset, an error is raised due to index out of range error...
**Describe the bug** In regression task, some category of mvtec dataset shows large performance drop before and after export, optimize, deploy **Steps to Reproduce** 1. Run regression test 2. 3....
**Describe the bug** Action detector trained on toy dataset shows 0.0 accuracy when it is exported. Fortunately, action detector trained on public dataset don't show this issue. **Steps to Reproduce**...
Got failures from the regression tests for the detetion task with tiling all failures are coming from Custom_Object_Detection_YOLOX template. ``` ================================================ short test summary info ================================================= FAILED tests/regression/detection/test_tiling_detection.py::TestRegressionTilingDetection::test_otx_train[Custom_Object_Detection_YOLOX] - AssertionError:...
**Describe the bug** https://github.com/openvinotoolkit/training_extensions/blob/develop/otx/algorithms/classification/adapters/mmcls/configurer.py#L632-L647 Current loss patching logic is dynamically and forcefully changing the loss type to either `CrossEntropy` or `IBLoss`. This code prevents the loss type from being updated...
Hi OTX team, Our results show that using Supervised Contrastive Loss shows decreased performance. I discussed this with Intel Labs, who noted that this might be caused by two things....
**Describe the bug** GPU memory increases although input image size decreases in instance segmentation. When I trained both instance segmentation model with 700x700 input size using wgisd-5 dataset, GPU memory...