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- # [first column]:model_name, If you need input shape, please connect it through ';' after the model name.
- # [second column]:accuracy limit in arm64
- # [third column]:accuracy limit in armv82_a32
- # Each column is separated by a space and comment on a single line!
- # The missing third column indicates that armv82_a32 does not need to maintain this model.
- age_medium 6
- beard 2
- emotion 60
- gender_res_large_deploy 0.1
- glasses 4
- hat 1
- isface 1
- ml_bank_detect_0312_tmp 20
- ml_face_div_parsing 8
- ml_hardware_eyeclose 0.1
- ml_ocr_detect_20200305 10
- Mnet6_0312_extract_pay 15
- pose_3d 90
- hiai_face_RFB-Epoch-170-no-transpose 4
- tracking 4
- mtk_landmark 1
- mtk_pose_tuku 1
- mtk_face_recognition_v1 20
- mtk_2012_ATLANTA_10class_20190614_v41 4
- mtk_detect-deeper-halfdeeper-mbv1-lastearlySSD-shortcut-400-400_nopostprocess_simplified 4
- # mtk_detect-deeper-halfdeeper-mbv1-shortcut-400-400_nopostprocess_simplified: precision is 5%
- detect-deeper-halfdeeper-mbv1-shortcut-400-400_nopostprocess_simplified 5.5
- hiai_face_detect_rfb 4
- hiai_face_isface 0.1
- hiai_face_landmark 0.2
- hiai_face_pose_tuku 1.3
- ml_hand_detection 8
- ml_ocr_cn 6
- ml_ocr_sfz_detect_0325_tmp 3
- ml_hardware_liveness 3
- ml_liveness_detect_landmark_tmp 1
- ml_face_contour 0.5
- 2012_ATLANTA_1class_20190621_v4.x_nomean 1
- ml_ocr_sfz_add_final_0325 0.1
- ml_hardware_pose 2
- ml_bank_recog 0.1
- 2012_ATLANTA_10class_20190131_v4.0 12
- mnet 9
- recognition 10
- ml_face_landmark 1
- model_hebing_3branch 40
- hiai_cv_focusShootOCRModel_07 3
- hiai_cv_focusShootOCRModel_03 60
- hiai_cv_focusShootOCRModel_01 14
- hiai_face_hat1 1
- hiai_cv_focusShootOCRModel_04 8
- hiai_cv_focusShootOCRModel_06 13
- hiai_cpu_face_hat 0.3
- hiai_video_seg 1
- hiai_semantic_seg 3
- hiai_human_seg 28
- hiai_face_recognition_1 10
- hiai_cpu_face_detect 4
- hiai_cpu_face_attr 12
- hiai_face_attr1 12
- # mtk_detect-mbv1-shortcut-400-400_nopostprocess_simplified: precision is 5%
- mtk_detect-mbv1-shortcut-400-400_nopostprocess_simplified 5.5
- mtk_detect_mbv1_640_480_nopostprocess_simplified 5
- retinaface 6
- deconv_test_model 20
- deconvs_model 1
- HWSR-s_256_256 10
- age_new 22
- detection_retinaface_fix 13
- landmark 1
- plat_isface 6
- PoseNet_dla_17_x512_tmp 5
- ml_location_scene_division 8
- ml_tabel_recog 0.1
- ml_text_division 12
- # Further analysis in the future to model ml_video_edit_Mnet
- ml_video_edit_Mnet 11
- ml_video_edit_hairSeg_have_imageProcessLayer_interpTo145 0.5
- hdc_age_medium 6
- hdc_contour_pose_128 0.5
- hdc_emotion 0.5
- hdc_fivembnet 0.5
- hdc_isface 0.5
- hdc_mobilenetface 7.5
- hdc_retinaface 14
- hdc_resnet 7
- ml_video_edit_detect 2.5
- ml_video_edit_hairSeg_have_imageProcessLayer_interpTo145_20210121 0.5
- ml_video_edit_have_imageProcessLayer_interpTo145_20201015 0.5
- ml_video_edit_MnetN367_extract_1010_pay 1
- ml_video_edit_person_divison_pic 0.5
- ml_video_edit_reid 1
- ml_video_edit_v10_best_model_nomean_20200723 5
- ml_video_edit_img_segment 3
- ml_video_edit_video_segment_gauss_adaptis_part1 5
- # When the input range is [-1,1], the precision is poor, and the output value is very small (10e-5). If the input range is adjusted to [0,255], the precision will decrease to 15.5415%, and the rest is cumulative error.
- ml_handpose 175
- hdc_Face_Aesthetic_MTI_Aesthetic 0.5
- ml_face_compare 5.5
- ml_face_tracking 2.5
- ml_face_beard 0.5
- ml_face_age 3.5
- ml_face_pose 1
- ml_face_isface 0.5
- ml_face_glasses 2.5
- # ml_segmentation_matting 26 # output value unstable
- ml_segmentation_atlanta_10 5
- # ml_bodymask: The difference of output node divided by a very small value leads to a large error
- ml_bodymask 14 13
- ml_Hand_deploy 4 4
- # ml_hand_3d_detection: The difference of output node divided by a very small value leads to a large error
- ml_hand_3d_detection 12 10
- ml_hand_3d_regression 3 4
- # ml_ARengine23_bodypose: The difference of output node divided by a very small value leads to a large error
- ml_ARengine23_bodypose 56 58
- ml_ocr_bank_card_detection_inception_tmp 20
- ml_ocr_bank_card_recognition_fcny 0.5
- hiai_cv_aestheticsEngineModel_osp 1.5
- ml_face_hat 0.5
- bank_card_recognition_fcny 17
- bank_card_detection_inception_tmp 12
- ml_ocr_identify_card_fcny 0.5
- ml_ocr_identify_card_detect_tmp 2
- identify_card_detect_tmp 0.5
- ml_2012_ocr_detection_caffe_tmp 1
- ml_2012_ocr_rec_caffe 0.5
- ml_lable_model_hebing_device 2
- ml_face_sex 0.5
- # ml_face_mnet: The precision problem caused by cumulative error.
- ml_face_mnet 12
- ml_segmentation_atlanta_1 0.5
- bolt_deploy_color-server 0.5
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