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Releases: CVHub520/X-AnyLabeling

X-AnyLabeling v2.5.1

16 Dec 06:44
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X-AnyLabeling v2.5.1 Pre-release
Pre-release

Coming soon...

X-AnyLabeling v2.5.0

15 Oct 14:32
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Released versions

Version MD5
X-AnyLabeling-CPU.exe e92cbfc03300c40312f5b4d4aa821200
X-Anylabeling-Linux-CPU 34f765b5cba2cd6a58ce05931045958a

Note

For GPU acceleration and the macOS version, please consult the guide at this link.
If you need to use the following advanced features, please refer to the corresponding documentation to install additional dependencies.

  1. Video object tracking based on Segment-Anything-2: Installation Guide
  2. Object proposal generation based on UPN: Installation Guide
  3. Interactive visual-text prompting for generic vision tasks: Installation Guide

Open Vision

Interactive Visual-Text Prompting for Generic Vision Tasks

Important updates

  • 🚀 feat(model): add support interactive visual-text prompting for generic vision tasks by @CVHub520 in 8f5768b
  • 🚀 feat(auto-labeling): optimize rectangle mode to use minimum bounding box by @CVHub520 in 4118efd
  • 🚀 feat(model): add support for SAM2.1 model by @CVHub520 in 812634d
  • 🚀 feat(model): add support for Florence-2 model (#679) by @CVHub520 in 67aac31
  • 🚀 feat(model): add support for the upn model to generate proposal boxes by @CVHub520 in 05eea0a
  • 🚀 feat(model): add support for yolov5-sahi model by @CVHub520 in 455b354
  • 🚀 feat(tool): add range selection for label batch modification (#708) by @CVHub520 in dcb7c51
  • 🚀 feat(export): add options dialog with additional export path selection (#702) by @CVHub520 in 398cb6b
  • 🚀 feat(import/export): add support for importing/exporting COCO keypoint annotations (#190) by @CVHub520 in 43cd1da
  • 🚀 feat(model): Added support for DocLayout-YOLO model
  • 🚀 feat(drawer): add option to color bounding boxes by category or instance by @CVHub520 in ba719c5
  • 🚀 feat(ui): add action to loop through each label by @julianstirling in 96f0617
  • 🐛 fix(import): handle invalid file paths in natural sort (#734) by @CVHub520 in 2b27a90
  • 🐛 fix(export): improve mask overlapping handling in custom_to_mask method by @CVHub520 in 2dd1968
  • 🐛 fix(tool): fix the path parsing error of the save_crop function by @wpNZC in 3a7c1e2
  • 🐛 fix(ui): disable delete action when no shapes present by @CVHub520 in 71d4cf2
  • 🐛 fix(model): correct image normalization in Recognize-Anything-Model preprocessing (#657) by @CVHub520 in 0b07dc4
  • 📚 docs(installation): add onnxruntime compatibility by @CVHub520 in 37e87a2
  • 🎨 refactor(ui): modernize GroupIDModifyDialog with improved styling by @CVHub520 in 7545561

Full Changelog: v2.4.4...v2.5.0

X-AnyLabeling v2.4.4

30 Sep 06:49
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Version MD5
X-AnyLabeling-CPU.exe d8d33f16e5afae68b410ad331c98d2da
X-Anylabeling-Linux-CPU 1e6746f82e095dcc22d51b11594adc96

Note

For GPU acceleration and the macOS version, please consult the guide at this link.
To use the video tracking feature with segment-anything-2, refer to the same document.

Important updates

image

Add support for YOLO11 Det/OBB/Pose/Seg/Track models

  • Integrate YOLO11 models from ultralytics v8.3.0
  • Enable detection, oriented bounding box, pose estimation, segmentation, and tracking functionalities
  • Update relevant documentation and dependencies)

Full Changelog: v2.4.3...v2.4.4

X-AnyLabeling v2.4.3

08 Sep 15:59
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Released versions

Version MD5
X-AnyLabeling-CPU.exe e51ee39db428686c6e1dfea53f80d148
X-Anylabeling-Linux-CPU 3d2a3751229e6a702b52862367306c4a

Note

For GPU acceleration and the macOS version, please consult the guide at this link.
To use the video tracking feature with segment-anything-2, refer to the same document.

Important updates

  • [Bug fixed] Ensure integer values for shape dimensions in show_shape signal by @CVHub520 in f974994
  • [Bug fixed] Fixed model loading error for YOLOv6lite face models (#638) by @CVHub520 in 995cf04
  • [Refactor] Enhance logging with bold and colored headers for better readability by @CVHub520 in 73a4288
  • [Model] Added support RMBG v1.4 model for image matting by @CVHub520 in 5a599e8
  • [Optimize]: Modify indexing operations to improve file navigation efficiency by @CVHub520 in e67a79f
  • [Optimize] Improve EXIF orientation handling with backup and logging by @CVHub520 in 59a73fa
  • [Optimize] Implement natural sorting for QListWidget labels (#627) by @CVHub520 in 3638fa9
  • [Optimize] Enable support for user-defined labels and track IDs (#629) by @CVHub520 in b173161

Full Changelog: v2.4.2...v2.4.3

X-AnyLabeling v2.4.2

06 Sep 15:46
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Released versions

Version MD5
X-AnyLabeling-CPU.exe 870548a8ef4310f811ec205ab625cdef
X-Anylabeling-Linux-CPU 2df31af95c868640afc199772cbbf6d6

Note

For GPU acceleration and the macOS version, please consult the guide at this link.
To use the video tracking feature with segment-anything-2, refer to the same document.

Important updates

  • [Model] Added support for interactive video object tracking by SAM2 (#602) by @CVHub520 in 0437e39
  • [Feature] Implement functionality to visualize drawing results @CVHub520 in cf8faf5
  • [Debug] Add vscode configuration files for module debugging and profiling by @CVHub520 in c807139
  • [Update] Fix typo in upload_coco_annotation function by @CVHub520 in 6be1cc2

Full Changelog: v2.4.1...v2.4.2

X-AnyLabeling v2.4.1

29 Aug 17:21
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Released versions

Version MD5
X-AnyLabeling-CPU.exe 99aafdfef8367fbe306425edae2745eb
X-Anylabeling-Linux-CPU 4c6358c7b6d1c0c3596b4c54e8ed6745

Note

To utilize GPU acceleration or the macOS version, refer to the guide at this.

Important updates

  • [Bug fixed] Fixed patch memory leak in image caching during image transitions by @CVHub520 in 5c498c2
  • [Bug fixed] Retain labels during switch model instances by @CVHub520 in 90217a9
  • [Feature] Add dialog for modifying group_id by @CVHub520 in 04b6298
  • [Feature] Add support to export mots annotations by @CVHub520 in da12032

Full Changelog: v2.4.0...v2.4.1

X-AnyLabeling v2.4.0

14 Jul 08:57
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Released versions

Version MD5
X-AnyLabeling-CPU.exe 8442c84cafdf6deddfe9e5fceb9af17e
X-Anylabeling-Linux-CPU b13829a34a1ff0f0b193c51fc4d951ea

Note

To utilize GPU acceleration or the macOS version, refer to the guide at this.

Supported models

Task Model
Image Classification ResNet50, InternImage, YOLOv5-cls, YOLOv8-cls, PULC Person/Vehicle Attribute
Object Detection YOLOv5, YOLOv6, YOLOv7, YOLOv8, YOLOv9, YOLOv10, YOLOX, YOLO-NAS, DAMO_YOLO, GOLD_YOLO, RT-DETR, RTMDet
Instance Segmentation YOLOv5-seg, YOLOv8-seg
Keypoint Detection RTMPose, DWPose, YOLOv6-face, YOLOv8-pose
Oriented Object Detection YOLOv5_obb, YOLOv8_obb
Multi-Object Tracking Bot-Sort, ByteTrack
Segment Anything SAM2, SAM, SAM-HQ, EdgeSAM, MobileSAM, EfficientViT-SAM, Med-SAM2D
Optical Character Recognition PPOCRv4
Land Detection CLRNet
Image Captioning RAM++, RAM
Visual Language Model Grounding-DINO, Chinese-CLIP, YOLO-World
Depth Estimation Depth Anything v2, Depth Anything

Important updates

New features

Docs

Bug fixed

  • Fixed image distortion issue during brightness and contrast adjustment by @CVHub520 in 252ded0
  • Fixed type error in fillRect by converting float values to int for compatibility with higher Python version by @CVHub520 in 71cfc30
  • Resolved too many values to unpack error during YOLO class post-process by @CVHub520 in a69077d
  • Fixed invalid literal for int() with base issue by @CVHub520 in 9380142
  • Avoided directory not empty error when loading model @CVHub520 in 599327b
  • Prevented crash when switching from image directory to imported image by @CVHub520 in 2402268
  • Fixed the issue where BMP image files could not be loaded due to the missing '_getexif' attribute by @UnlimitedWand in 6f64077

Full Changelog: v2.3.7...v2.4.0

X-AnyLabeling v2.3.7

29 May 14:54
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X-AnyLabeling v2.3.7 Pre-release
Pre-release

Supported models

Task Model
Image Classification ResNet50, InternImage, YOLOv5-cls, YOLOv8-cls, PULC Person/Vehicle Attribute
Object Detection YOLOv5, YOLOv6, YOLOv7, YOLOv8, YOLOv9, YOLOv10, YOLOX, YOLO-NAS, DAMO_YOLO, GOLD_YOLO, RT-DETR, RTMDet
Instance Segmentation YOLOv5-seg, YOLOv8-seg
Keypoint Detection RTMPose, DWPose, YOLOv6-face, YOLOv8-pose
Oriented Object Detection YOLOv5_obb, YOLOv8_obb
Multi-Object Tracking OC-Sort, ByteTrack
Segment Anything SAM, SAM-HQ, EdgeSAM, MobileSAM, EfficientViT-SAM, Med-SAM2D
Optical Character Recognition PPOCRv4
Land Detection CLRNet
Image Captioning RAM
Visual Language Model Grounding-DINO, Chinese-CLIP, YOLO-World
Depth Estimation Depth Anything

X-AnyLabeling v2.3.6

25 May 12:01
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Released versions

Version MD5
X-AnyLabeling-CPU.exe e1116910bf307c1eeee4cfb2e23cad99
X-AnyLabeling-GPU.exe c42b79aad0c77526fa0e155ad4f2b13c
X-Anylabeling-Linux-CPU b19c67157a971ddc7d6e3b69ca53d9c7
X-Anylabeling-Linux-GPU e5cfa26a75c1b77b50197bbc8b708087

Note: The GPU version mentioned above is compiled based on CUDA 11.6. Different versions may result in issues with xxx functionality. It is recommended to consider running the application using the source code, especially if compatibility issues arise.

Supported models

Task Model
Image Classification ResNet50, InternImage, YOLOv5-cls, YOLOv8-cls, PULC Person/Vehicle Attribute
Object Detection YOLOv5, YOLOv6, YOLOv7, YOLOv8, YOLOv9, YOLOv10, YOLOX, YOLO-NAS, DAMO_YOLO, GOLD_YOLO, RT-DETR, RTMDet
Instance Segmentation YOLOv5-seg, YOLOv8-seg
Keypoint Detection RTMPose, DWPose, YOLOv6-face, YOLOv8-pose
Oriented Object Detection YOLOv5_obb, YOLOv8_obb
Multi-Object Tracking OC-Sort, ByteTrack
Segment Anything SAM, SAM-HQ, EdgeSAM, MobileSAM, EfficientViT-SAM, Med-SAM2D
Optical Character Recognition PPOCRv4
Land Detection CLRNet
Image Captioning RAM
Visual Language Model Grounding-DINO, Chinese-CLIP, YOLO-World
Depth Estimation Depth Anything

Important Updates

X-AnyLabeling v2.3.5

01 Apr 13:58
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Released versions

Version MD5
X-AnyLabeling-CPU.exe 960a981d31231a6cc2af1a5ca108e1cb
X-AnyLabeling-GPU.exe fc8aaf1ff6133b0edc0a38b6553bf04a
X-Anylabeling-Linux-CPU cb69ed2b1e5e8c4daf273853631e7a5d
X-Anylabeling-Linux-GPU 7509bfcbc1ef7c85bdaf152c14030072

Note: The GPU version mentioned above is compiled based on CUDA 11.6. Different versions may result in issues with xxx functionality. It is recommended to consider running the application using the source code, especially if compatibility issues arise.

Supported models

Task Model
Image Classification ResNet50, InternImage, YOLOv5-cls, YOLOv8-cls, PULC Person/Vehicle Attribute
Object Detection YOLOv5, YOLOv6, YOLOv7, YOLOv8, YOLOv9, YOLOX, YOLO-NAS, DAMO_YOLO, GOLD_YOLO, RT-DETR, RTMDet
Instance Segmentation YOLOv5-seg, YOLOv8-seg
Keypoint Detection RTMPose, DWPose, YOLOv6-face, YOLOv8-pose
Oriented Object Detection YOLOv5_obb, YOLOv8_obb
Multi-Object Tracking OC-Sort, ByteTrack
Segment Anything SAM, SAM-HQ, EdgeSAM, MobileSAM, EfficientViT-SAM, Med-SAM2D
Optical Character Recognition PPOCRv4
Land Detection CLRNet
Image Captioning RAM
Visual Language Model Grounding-DINO, Chinese-CLIP, YOLO-World
Depth Estimation Depth Anything

Important Updates