返回模型
说明文档
这些模型基于 deepghs/anime_person_detection 和开源的真实照片数据集训练。
因此同时支持动漫和真实照片。
配合 dghs-realutils 使用:
pip install dghs-realutils
from realutils.detect import detect_persons
print(detect_persons('yolo/solo.jpg'))
#[((0, 30, 398, 599), 'person', 0.926707923412323)]
print(detect_persons('yolo/2girls.jpg'))
# [((0, 74, 760, 1598), 'person', 0.7578195333480835), ((437, 33, 1200, 1600), 'person', 0.6875205039978027)]
print(detect_persons('yolo/3+cosplay.jpg'))
# [((106, 69, 347, 591), 'person', 0.8794167041778564), ((326, 14, 592, 534), 'person', 0.8018194437026978), ((167, 195, 676, 675), 'person', 0.5351650714874268)]
print(detect_persons('yolo/multiple.jpg'))
# [((1305, 441, 1891, 1534), 'person', 0.8789498805999756), ((206, 191, 932, 1533), 'person', 0.8423126935958862), ((1054, 170, 1417, 1055), 'person', 0.8138357996940613), ((697, 659, 1473, 1534), 'person', 0.7926754951477051), ((685, 247, 1128, 1526), 'person', 0.5261526703834534), ((690, 251, 1125, 1126), 'person', 0.4193646311759949)]
更多信息请参阅 realutils 文档。
| 模型 | 类型 | FLOPS | 参数量 | F1 分数 | 阈值 | 精确率(B) | 召回率(B) | mAP50(B) | mAP50-95(B) | F1 曲线 | 混淆矩阵 | 标签 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| person_detect_v0_l_yv11 | yolo | 87.3G | 25.3M | 0.79 | 0.359 | 0.84037 | 0.74055 | 0.82796 | 0.57272 | 曲线 | 混淆矩阵 | person |
| person_detect_v0_m_yv11 | yolo | 68.2G | 20.1M | 0.78 | 0.351 | 0.83393 | 0.73614 | 0.82195 | 0.56267 | 曲线 | 混淆矩阵 | person |
| person_detect_v0_s_yv11 | yolo | 21.5G | 9.43M | 0.75 | 0.344 | 0.82356 | 0.6967 | 0.79224 | 0.52304 | 曲线 | 混淆矩阵 | person |
| person_detect_v0_n_yv11 | yolo | 6.44G | 2.59M | 0.71 | 0.325 | 0.80096 | 0.64148 | 0.74612 | 0.46875 | 曲线 | 混淆矩阵 | person |
| person_detect_v0_l | yolo | 165G | 43.6M | 0.79 | 0.359 | 0.83674 | 0.74182 | 0.82536 | 0.57022 | 曲线 | 混淆矩阵 | person |
| person_detect_v0_m | yolo | 79.1G | 25.9M | 0.78 | 0.363 | 0.83439 | 0.72529 | 0.81314 | 0.55388 | 曲线 | 混淆矩阵 | person |
| person_detect_v0_s | yolo | 28.6G | 11.1M | 0.76 | 0.346 | 0.82522 | 0.69696 | 0.79105 | 0.52201 | 曲线 | 混淆矩阵 | person |
| person_detect_v0_n | yolo | 8.19G | 3.01M | 0.72 | 0.32 | 0.80883 | 0.64552 | 0.74996 | 0.47272 | 曲线 | 混淆矩阵 | person |
deepghs/real_person_detection
作者 deepghs
object-detection
dghs-imgutils
↓ 0
♥ 3
创建时间: 2025-02-06 17:30:47+00:00
更新时间: 2025-02-20 11:21:36+00:00
在 Hugging Face 上查看文件 (130)
.gitattributes
README.md
person_detect_v0_l/F1_curve.png
person_detect_v0_l/PR_curve.png
person_detect_v0_l/P_curve.png
person_detect_v0_l/R_curve.png
person_detect_v0_l/confusion_matrix.png
person_detect_v0_l/confusion_matrix_normalized.png
person_detect_v0_l/events.out.tfevents.1738876259.74aa4261331bbcab0987b94433af8ac622a654e7594a46e49f97167a.3804866.0
person_detect_v0_l/labels.jpg
person_detect_v0_l/labels.json
person_detect_v0_l/labels_correlogram.jpg
person_detect_v0_l/model.onnx
ONNX
person_detect_v0_l/model.pt
person_detect_v0_l/model_type.json
person_detect_v0_l/results.csv
person_detect_v0_l/results.png
person_detect_v0_l/threshold.json
person_detect_v0_l_yv11/F1_curve.png
person_detect_v0_l_yv11/PR_curve.png
person_detect_v0_l_yv11/P_curve.png
person_detect_v0_l_yv11/R_curve.png
person_detect_v0_l_yv11/confusion_matrix.png
person_detect_v0_l_yv11/confusion_matrix_normalized.png
person_detect_v0_l_yv11/events.out.tfevents.1738898085.74aa4261331bbcab0987b94433af8ac622a654e7594a46e49f97167a.4177002.0
person_detect_v0_l_yv11/labels.jpg
person_detect_v0_l_yv11/labels.json
person_detect_v0_l_yv11/labels_correlogram.jpg
person_detect_v0_l_yv11/model.onnx
ONNX
person_detect_v0_l_yv11/model.pt
person_detect_v0_l_yv11/model_type.json
person_detect_v0_l_yv11/results.csv
person_detect_v0_l_yv11/results.png
person_detect_v0_l_yv11/threshold.json
person_detect_v0_m/F1_curve.png
person_detect_v0_m/PR_curve.png
person_detect_v0_m/P_curve.png
person_detect_v0_m/R_curve.png
person_detect_v0_m/confusion_matrix.png
person_detect_v0_m/confusion_matrix_normalized.png
person_detect_v0_m/events.out.tfevents.1738870487.74aa4261331bbcab0987b94433af8ac622a654e7594a46e49f97167a.3707067.0
person_detect_v0_m/labels.jpg
person_detect_v0_m/labels.json
person_detect_v0_m/labels_correlogram.jpg
person_detect_v0_m/model.onnx
ONNX
person_detect_v0_m/model.pt
person_detect_v0_m/model_type.json
person_detect_v0_m/results.csv
person_detect_v0_m/results.png
person_detect_v0_m/threshold.json
person_detect_v0_m_yv11/F1_curve.png
person_detect_v0_m_yv11/PR_curve.png
person_detect_v0_m_yv11/P_curve.png
person_detect_v0_m_yv11/R_curve.png
person_detect_v0_m_yv11/confusion_matrix.png
person_detect_v0_m_yv11/confusion_matrix_normalized.png
person_detect_v0_m_yv11/events.out.tfevents.1738891931.74aa4261331bbcab0987b94433af8ac622a654e7594a46e49f97167a.4072975.0
person_detect_v0_m_yv11/labels.jpg
person_detect_v0_m_yv11/labels.json
person_detect_v0_m_yv11/labels_correlogram.jpg
person_detect_v0_m_yv11/model.onnx
ONNX
person_detect_v0_m_yv11/model.pt
person_detect_v0_m_yv11/model_type.json
person_detect_v0_m_yv11/results.csv
person_detect_v0_m_yv11/results.png
person_detect_v0_m_yv11/threshold.json
person_detect_v0_n/F1_curve.png
person_detect_v0_n/PR_curve.png
person_detect_v0_n/P_curve.png
person_detect_v0_n/R_curve.png
person_detect_v0_n/confusion_matrix.png
person_detect_v0_n/confusion_matrix_normalized.png
person_detect_v0_n/events.out.tfevents.1738863182.74aa4261331bbcab0987b94433af8ac622a654e7594a46e49f97167a.3578579.0
person_detect_v0_n/labels.jpg
person_detect_v0_n/labels.json
person_detect_v0_n/labels_correlogram.jpg
person_detect_v0_n/model.onnx
ONNX
person_detect_v0_n/model.pt
person_detect_v0_n/model_type.json
person_detect_v0_n/results.csv
person_detect_v0_n/results.png
person_detect_v0_n/threshold.json
person_detect_v0_n_yv11/F1_curve.png
person_detect_v0_n_yv11/PR_curve.png
person_detect_v0_n_yv11/P_curve.png
person_detect_v0_n_yv11/R_curve.png
person_detect_v0_n_yv11/confusion_matrix.png
person_detect_v0_n_yv11/confusion_matrix_normalized.png
person_detect_v0_n_yv11/events.out.tfevents.1738884045.74aa4261331bbcab0987b94433af8ac622a654e7594a46e49f97167a.3934536.0
person_detect_v0_n_yv11/labels.jpg
person_detect_v0_n_yv11/labels.json
person_detect_v0_n_yv11/labels_correlogram.jpg
person_detect_v0_n_yv11/model.onnx
ONNX
person_detect_v0_n_yv11/model.pt
person_detect_v0_n_yv11/model_type.json
person_detect_v0_n_yv11/results.csv
person_detect_v0_n_yv11/results.png
person_detect_v0_n_yv11/threshold.json
person_detect_v0_s/F1_curve.png
person_detect_v0_s/PR_curve.png
person_detect_v0_s/P_curve.png
person_detect_v0_s/R_curve.png
person_detect_v0_s/confusion_matrix.png
person_detect_v0_s/confusion_matrix_normalized.png
person_detect_v0_s/events.out.tfevents.1738866493.74aa4261331bbcab0987b94433af8ac622a654e7594a46e49f97167a.3637442.0
person_detect_v0_s/labels.jpg
person_detect_v0_s/labels.json
person_detect_v0_s/labels_correlogram.jpg
person_detect_v0_s/model.onnx
ONNX
person_detect_v0_s/model.pt
person_detect_v0_s/model_type.json
person_detect_v0_s/results.csv
person_detect_v0_s/results.png
person_detect_v0_s/threshold.json
person_detect_v0_s_yv11/F1_curve.png
person_detect_v0_s_yv11/PR_curve.png
person_detect_v0_s_yv11/P_curve.png
person_detect_v0_s_yv11/R_curve.png
person_detect_v0_s_yv11/confusion_matrix.png
person_detect_v0_s_yv11/confusion_matrix_normalized.png
person_detect_v0_s_yv11/events.out.tfevents.1738887778.74aa4261331bbcab0987b94433af8ac622a654e7594a46e49f97167a.4000812.0
person_detect_v0_s_yv11/labels.jpg
person_detect_v0_s_yv11/labels.json
person_detect_v0_s_yv11/labels_correlogram.jpg
person_detect_v0_s_yv11/model.onnx
ONNX
person_detect_v0_s_yv11/model.pt
person_detect_v0_s_yv11/model_type.json
person_detect_v0_s_yv11/results.csv
person_detect_v0_s_yv11/results.png
person_detect_v0_s_yv11/threshold.json