anaksor-ocr
Sokheng · Kit
Reads Khmer and English text from documents, receipts and photos of signs, using a detector for text lines and a recogniser for each line. Suits developers who…
Turns a photo into an OpenPose-style pose map, built to handle several overlapping people in one frame. The maps work as control images for ControlNet pose models. Runs on CPU.
Pose Skeleton Multi-Orang (DWPose/RTMW) is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on . Download it on this page, a zip of its files. Nothing in it runs by itself.
pip install -U huggingface_hub hf download kulkas2pintu/pose-skeleton-multi --repo-type space --local-dir pose-skeleton-multi cd pose-skeleton-multi
This Space turns a photo into an OpenPose-style pose map on a black background, with 18 body points, 21 points per hand and 68 face points. You use the map as a control image for a ControlNet pose model. It focuses on photos where several people overlap, which ordinary pipelines handle badly.
People who make images with pose-controlled generators, and developers who want pose detection that keeps overlapping people instead of dropping them.
| Industry | Who uses it | How they use it | Example |
|---|---|---|---|
| Image generation | Digital artists | Make a pose map from a reference photo for a ControlNet model | Upload a group photo and download the map |
| Design | Illustrators | Capture the pose of several people in one frame | Check the overlay with numbered people |
| Software | Developers | Study a pose pipeline that merges duplicates at pose level | Read pose_engine.py |
| Research | Computer vision students | Compare detection settings on crowded scenes | Change the target person count and rerun |
Anyone who only needs single-person pose or a plain photo editor can skip it.
It runs in these places, and its outputs feed other tools.
| Use case | Who | What they get back |
|---|---|---|
| Make a pose map | Artists | A black-background PNG you can download |
| Check the detection | Reviewers | An overlay with the skeleton, boxes and person numbers |
| Export keypoints | Developers | JSON in OpenPose format |
Using the Space online needs only a browser. A copy on your own computer needs the following.
pip install -U huggingface_hub hf download kulkas2pintu/pose-skeleton-multi --repo-type space --local-dir pose-skeleton-multi cd pose-skeleton-multi pip install gradio==5.49.1 pip install -r requirements.txt python app.py
Open the Space's page, or run the app on your computer and open the page Gradio shows. Upload a photo with one or more people, optionally set the number of people you expect, and run it. Then download the outputs.
python app.py
| Tool | What it does |
|---|---|
| Pose map | The black-background skeleton image, ready for ControlNet |
| Overlay | The photo with skeletons, boxes and person numbers |
| JSON keypoints | OpenPose-format data for ComfyUI or OpenPose Editor |
| Target person count | Pulls in the best low-scoring candidates when too few people pass the strict threshold |
You upload a photo of two people hugging and set the target to 2. The Space returns a pose map with both skeletons, an overlay that numbers each person, and a JSON file of keypoints.
A pose map is a stick-figure picture of where each body part is. Image generators can follow it to copy a pose. The first small thing to try is the online Space with a clear photo of two people.
Standard top-down pipelines detect people, then find a pose in each box. They lose overlapping people because the detector drops the second box and a score cut-off removes partly seen people. This Space uses a minimal score cut-off and a looser box overlap limit of 0.75. It removes duplicates by comparing poses with OKS, and it drops stolen keypoints.
All models run on CPU through ONNX Runtime, and a GPU is used when one is available.
Turns a photo into an OpenPose-style pose map, built to handle several overlapping people in one frame. The maps work as control images for ControlNet pose models. Runs on CPU.
Made by kulkas2pintu on Hugging Face. These notes are Mindket's, written from its Space page and README; the app's own files and license are on Hugging Face.
What it is: This Space turns a photo into an OpenPose-style pose map on a black background, with 18 body points, 21 points per hand and 68 face points. You use the map as a control image for a ControlNet pose model. It focuses on photos where several people overlap, which ordinary pipelines handle badly.
Who it suits: People who make images with pose-controlled generators, and developers who want pose detection that keeps overlapping people instead of dropping them.
Industry | Who uses it | How they use it | Example
Image generation | Digital artists | Make a pose map from a reference photo for a ControlNet model | Upload a group photo and download the map
Design | Illustrators | Capture the pose of several people in one frame | Check the overlay with numbered people
Software | Developers | Study a pose pipeline that merges duplicates at pose level | Read pose_engine.py
Research | Computer vision students | Compare detection settings on crowded scenes | Change the target person count and rerun
Anyone who only needs single-person pose or a plain photo editor can skip it.
Where to use it: It runs in these places, and its outputs feed other tools.
Use case | Who | What they get back
Make a pose map | Artists | A black-background PNG you can download
Check the detection | Reviewers | An overlay with the skeleton, boxes and person numbers
Export keypoints | Developers | JSON in OpenPose format
How to set it up: Using the Space online needs only a browser. A copy on your own computer needs the following.
pip install -U huggingface_hub
hf download kulkas2pintu/pose-skeleton-multi --repo-type space --local-dir pose-skeleton-multi
cd pose-skeleton-multi
pip install gradio==5.49.1
pip install -r requirements.txt
python app.py
How to use it: Open the Space's page, or run the app on your computer and open the page Gradio shows. Upload a photo with one or more people, optionally set the number of people you expect, and run it. Then download the outputs.
python app.py
Tool | What it does
Pose map | The black-background skeleton image, ready for ControlNet
Overlay | The photo with skeletons, boxes and person numbers
JSON keypoints | OpenPose-format data for ComfyUI or OpenPose Editor
Target person count | Pulls in the best low-scoring candidates when too few people pass the strict threshold
Example: You upload a photo of two people hugging and set the target to 2. The Space returns a pose map with both skeletons, an overlay that numbers each person, and a JSON file of keypoints.
For newcomers and experts: A pose map is a stick-figure picture of where each body part is. Image generators can follow it to copy a pose. The first small thing to try is the online Space with a clear photo of two people.
Standard top-down pipelines detect people, then find a pose in each box. They lose overlapping people because the detector drops the second box and a score cut-off removes partly seen people. This Space uses a minimal score cut-off and a looser box overlap limit of 0.75. It removes duplicates by comparing poses with OKS, and it drops stolen keypoints.
YOLOX finds candidate people with loose limits
RTMW or DWPose finds 133 whole-body points
OKS removes duplicate poses
The pose map, overlay and JSON are returned
Good to know: All models run on CPU through ONNX Runtime, and a GPU is used when one is available.
Open the Space in your browser, or copy it to your own Hugging Face account from its page. Nothing in this kit runs by itself.
README.md 5 KB
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