Duplicate from sshao0516/CrowdHuman

Co-authored-by: Shuai Shao <sshao0516@users.noreply.huggingface.co>

.gitattributes

@@ -0,0 +1,61 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.lz4 filter=lfs diff=lfs merge=lfs -text
+*.mds filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+# Audio files - uncompressed
+*.pcm filter=lfs diff=lfs merge=lfs -text
+*.sam filter=lfs diff=lfs merge=lfs -text
+*.raw filter=lfs diff=lfs merge=lfs -text
+# Audio files - compressed
+*.aac filter=lfs diff=lfs merge=lfs -text
+*.flac filter=lfs diff=lfs merge=lfs -text
+*.mp3 filter=lfs diff=lfs merge=lfs -text
+*.ogg filter=lfs diff=lfs merge=lfs -text
+*.wav filter=lfs diff=lfs merge=lfs -text
+# Image files - uncompressed
+*.bmp filter=lfs diff=lfs merge=lfs -text
+*.gif filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text
+*.tiff filter=lfs diff=lfs merge=lfs -text
+# Image files - compressed
+*.jpg filter=lfs diff=lfs merge=lfs -text
+*.jpeg filter=lfs diff=lfs merge=lfs -text
+*.webp filter=lfs diff=lfs merge=lfs -text
+# Video files - compressed
+*.mp4 filter=lfs diff=lfs merge=lfs -text
+*.webm filter=lfs diff=lfs merge=lfs -text
+annotation_train.odgt filter=lfs diff=lfs merge=lfs -text
+annotation_val.odgt filter=lfs diff=lfs merge=lfs -text

CrowdHuman_test.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4d43213edab47ca26d36bd1a8438f859da45b74e160c4d147871426d95914213
+size 3259241265

CrowdHuman_train01.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7ba340163cff0f2446027af95dc96bcb9c66be18506eabb57822c400a7efd3b8
+size 2970597373

CrowdHuman_train02.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d9ecfb43eaf8381ddd4d1ff4e9a0877b694dbfba7a7a33ed3966ee2c2a628663
+size 3092749718

CrowdHuman_train03.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9cac171914c4f5c7371e3d42d20b50858caa1602811ae573aa35bbfe672dc29f
+size 2306357030

CrowdHuman_val.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c0ab99bb80ac162cd3efdf94a1a6100c4f059a61d69596412c6b44ebc20d1363
+size 2488658160

README.md

@@ -0,0 +1,104 @@
+---
+license: cc-by-nc-4.0
+task_categories:
+- object-detection
+language:
+- en
+pretty_name: CrowdHuman
+size_categories:
+- 10K<n<100K
+---
+# CrowdHuman: A Benchmark for Detecting Human in a Crowd
+
+- 🏠 homepage: https://www.crowdhuman.org/
+- 📄 paper: https://arxiv.org/pdf/1805.00123
+
+CrowdHuman is a benchmark dataset to better evaluate detectors in crowd scenarios. The CrowdHuman dataset is large, rich-annotated and contains high diversity. CrowdHuman contains 15000, 4370 and 5000 images for training, validation, and testing, respectively. There are a total of 470K human instances from train and validation subsets and 23 persons per image, with various kinds of occlusions in the dataset. Each human instance is annotated with a head bounding-box, human visible-region bounding-box and human full-body bounding-box. We hope our dataset will serve as a solid baseline and help promote future research in human detection tasks.
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/6548f8779be7bd365d04ab91/Gpvj5Yu8QUzxeUIJhGrmJ.png)
+*Volume, density and diversity of different human detection datasets. For fair comparison, we only show the statistics of training subset.*
+
+## 🔍 Samples
+
+|![image/png](https://cdn-uploads.huggingface.co/production/uploads/6548f8779be7bd365d04ab91/dPyyTwCTTZIE2cHRAZmNn.png)|![image/png](https://cdn-uploads.huggingface.co/production/uploads/6548f8779be7bd365d04ab91/rsZAVFTtcocma-Fl7C_QI.png)|![image/png](https://cdn-uploads.huggingface.co/production/uploads/6548f8779be7bd365d04ab91/MQxjxtQap5hGs6FtxXs1_.png)|
+|:--:|:--:|:--:|
+|![image/png](https://cdn-uploads.huggingface.co/production/uploads/6548f8779be7bd365d04ab91/hcpWVRx6l5HAcLyg8XmxB.png)|![image/png](https://cdn-uploads.huggingface.co/production/uploads/6548f8779be7bd365d04ab91/csivXdrgg_znDNh3quDTR.png)|![image/png](https://cdn-uploads.huggingface.co/production/uploads/6548f8779be7bd365d04ab91/RRPrpesNDYG7hNf2RuWMT.png)|
+|![image/png](https://cdn-uploads.huggingface.co/production/uploads/6548f8779be7bd365d04ab91/-4ejs7lZGP9jhG8qBIQV2.png)|![image/png](https://cdn-uploads.huggingface.co/production/uploads/6548f8779be7bd365d04ab91/gAgUfdpj86vw4f_ovb6hT.png)|![image/png](https://cdn-uploads.huggingface.co/production/uploads/6548f8779be7bd365d04ab91/T-0bunDoidqaShROa3eKI.png)|
+
+## 📁 Files
+- `CrowdHuman_train01.zip`
+- `CrowdHuman_train02.zip`
+- `CrowdHuman_train03.zip`
+- `CrowdHuman_val.zip`
+- `CrowdHuman_test.zip`
+- `annotation_train.odgt`
+- `annotation_val.odgt`
+
+## 🖨 Data Format
+We support `annotation_train.odgt` and `annotation_val.odgt` which contains the annotations of our dataset.
+
+### What is odgt?
+`odgt` is a file format that each line of it is a JSON, this JSON contains the whole annotations for the relative image. We prefer using this format since it is reader-friendly.
+
+### Annotation format
+```json
+JSON{
+    "ID" : image_filename,
+    "gtboxes" : [gtbox], 
+}
+
+gtbox{
+    "tag" : "person" or "mask", 
+    "vbox": [x, y, w, h],
+    "fbox": [x, y, w, h],
+    "hbox": [x, y, w, h],
+    "extra" : extra, 
+    "head_attr" : head_attr, 
+}
+
+extra{
+    "ignore": 0 or 1,
+    "box_id": int,
+    "occ": int,
+}
+
+head_attr{
+    "ignore": 0 or 1,
+    "unsure": int,
+    "occ": int,
+}
+```
+- `Keys` in `extra` and `head_attr` are **optional**, it means some of them may not exist
+- `extra/head_attr` contains attributes for `person/head`
+- `tag` is `mask` means that this box is `crowd/reflection/something like person/...` and need to be `ignore`(the `ignore` in `extra` is `1`)
+- `vbox, fbox, hbox` means `visible box, full box, head box` respectively
+
+## ⚠️ Terms of use:
+by downloading the image data you agree to the following terms:
+1. You will use the data only for non-commercial research and educational purposes.
+2. You will NOT distribute the above images.
+3. Megvii Technology makes no representations or warranties regarding the data, including but not limited to warranties of non-infringement or fitness for a particular purpose.
+4. You accept full responsibility for your use of the data and shall defend and indemnify Megvii Technology, including its employees, officers and agents, against any and all claims arising from your use of the data, including but not limited to your use of any copies of copyrighted images that you may create from the data.
+
+## 🏆 Related Challenge
+- [Detection In the Wild Challenge Workshop 2019](https://www.objects365.org/workshop2019.html)
+
+## 📚 Citaiton
+Please cite the following paper if you use our dataset.
+```
+@article{shao2018crowdhuman,
+  title={CrowdHuman: A Benchmark for Detecting Human in a Crowd},
+  author={Shao, Shuai and Zhao, Zijian and Li, Boxun and Xiao, Tete and Yu, Gang and Zhang, Xiangyu and Sun, Jian},
+  journal={arXiv preprint arXiv:1805.00123},
+  year={2018}
+}
+```
+
+## 👥 People
+- [Shuai Shao*](https://www.sshao.com/)
+- [Zijian Zhao*](https://scholar.google.com/citations?user=9Iv3NoIAAAAJ)
+- Boxun Li
+- [Tete Xiao](https://tetexiao.com/)
+- [Gang Yu](https://www.skicyyu.org/)
+- [Xiangyu Zhang](https://scholar.google.com/citations?user=yuB-cfoAAAAJ)
+- [Jian Sun](https://scholar.google.com/citations?user=ALVSZAYAAAAJ)

annotation_train.odgt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6bf241a79f19e30cf52681eab3392368bd5a534164be9272e7a808cb284d9f77
+size 80017502

annotation_val.odgt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:be422c79a190ff7e30fe5cbd74cbf45a2dadda6c5af58c6ec11a038ba2993c04
+size 23323139