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: My Code 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("============================================================") Input Image : here is my input image Output 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 OS : Windows 10 GPU : RTX 4090 24G Python : 3.9.21 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 Continue reading...
