Insightface人脸检测返回空列表问题排查求助

阿华AIGC实验室

2026-4-15

我最近用Insightface做图片人脸检测时碰上个棘手的问题——检测结果直接返回了空列表，完全识别不到图片里的人脸。我检查了代码的基本逻辑，也确认了图片能正常读取，但还是找不到问题根源，想请大家帮忙一起排查下哪里出了问题？

我的代码

import cv2
from insightface.app import FaceAnalysis
from insightface.data import get_image

app = FaceAnalysis(providers=['CUDAExecutionProvider', 'CPUExecutionProvider'])
app.prepare(ctx_id=0, det_size=(640, 640))
img = cv2.imread("face.jpg")
faces = app.get(img)
print("============================================================")
print(faces)
print("============================================================")

输入图片

输入的是一张包含正面人脸的图片，人物面部清晰，没有明显遮挡。

运行输出

Applied providers: ['CUDAExecutionProvider', 'CPUExecutionProvider'], with options: {'CUDAExecutionProvider': {'device_id': '0', 'has_user_compute_stream': '0', 'cudnn_conv1d_pad_to_nc1d': '0', 'user_compute_stream': '0', 'gpu_external_alloc': '0', 'gpu_mem_limit': '18446744073709551615', 'enable_cuda_graph': '0', 'gpu_external_free': '0', 'gpu_external_empty_cache': '0', 'arena_extend_strategy': 'kNextPowerOfTwo', 'cudnn_conv_algo_search': 'EXHAUSTIVE', 'do_copy_in_default_stream': '1', 'cudnn_conv_use_max_workspace': '1', 'tunable_op_enable': '0', 'tunable_op_tuning_enable': '0', 'tunable_op_max_tuning_duration_ms': '0', 'enable_skip_layer_norm_strict_mode': '0', 'prefer_nhwc': '0', 'use_ep_level_unified_stream': '0', 'use_tf32': '1', 'sdpa_kernel': '0'}, 'CPUExecutionProvider': {}}
find model: C:\Users\iii_a/.insightface\models\buffalo_l\1k3d68.onnx landmark_3d_68 ['None', 3, 192, 192] 0.0 1.0
Applied providers: ['CUDAExecutionProvider', 'CPUExecutionProvider'], with options: {'CUDAExecutionProvider': {'device_id': '0', 'has_user_compute_stream': '0', 'cudnn_conv1d_pad_to_nc1d': '0', 'user_compute_stream': '0', 'gpu_external_alloc': '0', 'gpu_mem_limit': '18446744073709551615', 'enable_cuda_graph': '0', 'gpu_external_free': '0', 'gpu_external_empty_cache': '0', 'arena_extend_strategy': 'kNextPowerOfTwo', 'cudnn_conv_algo_search': 'EXHAUSTIVE', 'do_copy_in_default_stream': '1', 'cudnn_conv_use_max_workspace': '1', 'tunable_op_enable': '0', 'tunable_op_tuning_enable': '0', 'tunable_op_max_tuning_duration_ms': '0', 'enable_skip_layer_norm_strict_mode': '0', 'prefer_nhwc': '0', 'use_ep_level_unified_stream': '0', 'use_tf32': '1', 'sdpa_kernel': '0'}, 'CPUExecutionProvider': {}}
find model: C:\Users\iii_a/.insightface\models\buffalo_l\2d106det.onnx landmark_2d_106 ['None', 3, 192, 192] 0.0 1.0
Applied providers: ['CUDAExecutionProvider', 'CPUExecutionProvider'], with options: {'CUDAExecutionProvider': {'device_id': '0', 'has_user_compute_stream': '0', 'cudnn_conv1d_pad_to_nc1d': '0', 'user_compute_stream': '0', 'gpu_external_alloc': '0', 'gpu_mem_limit': '18446744073709551615', 'enable_cuda_graph': '0', 'gpu_external_free': '0', 'gpu_external_empty_cache': '0', 'arena_extend_strategy': 'kNextPowerOfTwo', 'cudnn_conv_algo_search': 'EXHAUSTIVE', 'do_copy_in_default_stream': '1', 'cudnn_conv_use_max_workspace': '1', 'tunable_op_enable': '0', 'tunable_op_tuning_enable': '0', 'tunable_op_max_tuning_duration_ms': '0', 'enable_skip_layer_norm_strict_mode': '0', 'prefer_nhwc': '0', 'use_ep_level_unified_stream': '0', 'use_tf32': '1', 'sdpa_kernel': '0'}, 'CPUExecutionProvider': {}}
find model: C:\Users\iii_a/.insightface\models\buffalo_l\det_10g.onnx detection [1, 3, '?', '?'] 127.5 128.0
Applied providers: ['CUDAExecutionProvider', 'CPUExecutionProvider'], with options: {'CUDAExecutionProvider': {'device_id': '0', 'has_user_compute_stream': '0', 'cudnn_conv1d_pad_to_nc1d': '0', 'user_compute_stream': '0', 'gpu_external_alloc': '0', 'gpu_mem_limit': '18446744073709551615', 'enable_cuda_graph': '0', 'gpu_external_free': '0', 'gpu_external_empty_cache': '0', 'arena_extend_strategy': 'kNextPowerOfTwo', 'cudnn_conv_algo_search': 'EXHAUSTIVE', 'do_copy_in_default_stream': '1', 'cudnn_conv_use_max_workspace': '1', 'tunable_op_enable': '0', 'tunable_op_tuning_enable': '0', 'tunable_op_max_tuning_duration_ms': '0', 'enable_skip_layer_norm_strict_mode': '0', 'prefer_nhwc': '0', 'use_ep_level_unified_stream': '0', 'use_tf32': '1', 'sdpa_kernel': '0'}, 'CPUExecutionProvider': {}}
find model: C:\Users\iii_a/.insightface\models\buffalo_l\genderage.onnx genderage ['None', 3, 96, 96] 0.0 1.0
Applied providers: ['CUDAExecutionProvider', 'CPUExecutionProvider'], with options: {'CUDAExecutionProvider': {'device_id': '0', 'has_user_compute_stream': '0', 'cudnn_conv1d_pad_to_nc1d': '0', 'user_compute_stream': '0', 'gpu_external_alloc': '0', 'gpu_mem_limit': '18446744073709551615', 'enable_cuda_graph': '0', 'gpu_external_free': '0', 'gpu_external_empty_cache': '0', 'arena_extend_strategy': 'kNextPowerOfTwo', 'cudnn_conv_algo_search': 'EXHAUSTIVE', 'do_copy_in_default_stream': '1', 'cudnn_conv_use_max_workspace': '1', 'tunable_op_enable': '0', 'tunable_op_tuning_enable': '0', 'tunable_op_max_tuning_duration_ms': '0', 'enable_skip_layer_norm_strict_mode': '0', 'prefer_nhwc': '0', 'use_ep_level_unified_stream': '0', 'use_tf32': '1', 'sdpa_kernel': '0'}, 'CPUExecutionProvider': {}}
find model: C:\Users\iii_a/.insightface\models\buffalo_l\w600k_r50.onnx recognition ['None', 3, 112, 112] 127.5 127.5
set det-size: (640, 640)
============================================================
[]
============================================================

我的运行环境

操作系统：Windows 10
GPU：RTX 4090 24G
Python版本：3.9.21
核心依赖包版本：

Package                Version
---------------------- -----------
albucore               0.0.23
albumentations         2.0.0
annotated-types        0.7.0
antlr4-python3-runtime 4.9.3
certifi                2024.12.14
charset-normalizer     3.4.1
colorama               0.4.6
coloredlogs            15.0.1
contourpy              1.3.0
cycler                 0.12.1
Cython                 3.0.11
easydict               1.13
eval_type_backport     0.2.2
filelock               3.16.1
flatbuffers            24.12.23
fonttools              4.55.3
fsspec                 2024.12.0
humanfriendly          10.0
idna                   3.10
imageio                2.37.0
importlib_resources    6.5.2
insightface            0.7.3
Jinja2                 3.1.5
joblib                 1.4.2
kiwisolver             1.4.7
lap                    0.5.12
lazy_loader            0.4
MarkupSafe             3.0.2
matplotlib             3.9.4
mpmath                 1.3.0
networkx               3.2.1
numpy                  2.0.2
omegaconf              2.3.0
onnx                   1.17.0
onnxruntime-gpu        1.19.2
opencv-python          4.11.0.86
opencv-python-headless 4.11.0.86
packaging              24.2
pandas                 2.2.3
pillow                 11.1.0
pip                    24.2
prettytable            3.12.0
protobuf               5.29.3
psutil                 6.1.1
py-cpuinfo             9.0.0
pydantic               2.10.5
pydantic_core          2.27.2
pyparsing              3.2.1
pyreadline3            3.5.4
python-dateutil        2.9.0.post0
pytz                   2024.2
PyYAML                 6.0.2
requests               2.32.3
scikit-image           0.24.0
scikit-learn           1.6.1
scipy                  1.13.1
seaborn                0.13.2
setuptools             75.1.0
simsimd                6.2.1
six                    1.17.0
stringzilla            3.11.3
sympy                  1.13.1
threadpoolctl          3.5.0
tifffile               2024.8.30
torch                  2.5.1
torchvision            0.20.1
tqdm                   4.67.1
typing_extensions      4.12.2
tzdata                 2024.2
ultralytics            8.3.64
ultralytics-thop       2.0.14
urllib3                2.3.0
wcwidth                0.2.13
wheel                  0.44.0
zipp                   3.21.0

我已经确认过cv2.imread("face.jpg")没有返回None，图片确实被正常读取了，模型加载的日志看起来也没有报错，但就是检测不到人脸。有没有朋友遇到过类似情况，或者能给我一些排查的方向？

备注：内容来源于stack exchange，提问作者Nick Wu