pythonartificial-intelligenceinsightface

insightface cannot recognize faces

I used Insightface to detect a face in an image, but the detection result was an empty list (unable to detect any faces). Could you help identify which part might have gone wrong? Here are the code and the input/output:

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("============================================================")

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)
============================================================
[]
============================================================

Here are my python versions and python packages

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
Solution

  • It is recommended not to put just the face alone, but to have some external features, which can make the AI ​​model recognize it better. The following is a reference picture that you can use and test.

    Reference pictures

    enter image description here