!15398 add model commit

From: @wangyanling10
Reviewed-by: @jpc_chenjianping,@zhang_xue_tong
Signed-off-by: @jpc_chenjianping,@zhang_xue_tong

mindspore/lite/test/models_caffe.cfg

@@ -11,7 +11,7 @@ ml_hardware_eyeclose
 ml_ocr_detect_20200305
 Mnet6_0312_extract_pay
 pose_3d
-RFB-Epoch-170-no-transpose
+hiai_face_RFB-Epoch-170-no-transpose
 tracking
 mtk_isface
 mtk_landmark
@@ -53,8 +53,8 @@ hiai_face_recognition_1
 hiai_cpu_face_detect
 hiai_cpu_face_attr
 hiai_face_attr1
-detect-mbv1-shortcut-400-400_nopostprocess_simplified
-detect_mbv1_640_480_nopostprocess_simplified
+mtk_detect-mbv1-shortcut-400-400_nopostprocess_simplified
+mtk_detect_mbv1_640_480_nopostprocess_simplified
 retinaface
 deconv_test_model
 deconvs_model

mindspore/lite/test/models_caffe_fp16.cfg

@@ -11,14 +11,15 @@ ml_hardware_eyeclose 0.1
 ml_ocr_detect_20200305 10
 Mnet6_0312_extract_pay 15
 pose_3d 90
-RFB-Epoch-170-no-transpose 4
+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
-detect-deeper-halfdeeper-mbv1-shortcut-400-400_nopostprocess_simplified 1
+# 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
@@ -52,8 +53,9 @@ hiai_face_recognition_1 10
 hiai_cpu_face_detect 4
 hiai_cpu_face_attr 12
 hiai_face_attr1 12
-detect-mbv1-shortcut-400-400_nopostprocess_simplified 8
-detect_mbv1_640_480_nopostprocess_simplified 6
+# 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
@@ -85,6 +87,7 @@ 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 22
 ml_face_compare 5.5
@@ -96,10 +99,13 @@ 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
 ml_Hand_deploy 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
 ml_hand_3d_regression 3
+# ml_ARengine23_bodypose: The difference of output node divided by a very small value leads to a large error
 ml_ARengine23_bodypose 56
 ml_ocr_bank_card_detection_inception_tmp 20
 ml_ocr_bank_card_recognition_fcny 0.5
@@ -114,6 +120,7 @@ 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

mindspore/lite/test/models_for_process_only.cfg

@@ -24,4 +24,5 @@ quant_aware_identify_card_detect.onnx
 tiny-yolov3-11.onnx;2;1,416,416,3:1,2
 # cur acc for ml_video_edit_art_transfer is 2+%
 ml_video_edit_art_transfer.onnx;3
+#ml_table_detection.onnx: onnx quantized model
 ml_table_detection.onnx

mindspore/lite/test/models_tf_fp16.cfg

@@ -2,26 +2,30 @@ ml_vision_guide_detection1.pb 0.5
 ml_vision_guide_detection3.pb 0.5
 ml_video_edit_generate_filter.pb 2
 ml_ocr_jk.pb 0.5
-ml_ocr_latin.pb 135
+# The accumulated error causes the threshold to be exceeded
+ml_ocr_latin.pb 12
 scan_hms_angle.pb 1.5
 scan_hms_detect.pb 2.5
 ml_face_openclose.pb;1,32,32,3 0.5
 ml_object_detect.pb;1,288,288,3 2
-# the inputs of two Q_crnn_screen_slim400w models are between 0-255, but their outputs have small values (e-7).
+# The inputs of two Q_crnn_screen_slim400w models are between 0-255, but their outputs have small values (e-7).
 Q_crnn_screen_slim400w_more_20w.pb 72
 Q_inception-249970-672-11-16.pb 6.5
 hiai_ssd_mobilenetv2_object.pb 15
 hiai_humanDetection.pb 3.5
 hiai_PoseEstimation_Pcm.pb 0.5
+# The last layer has a very small value, which leads to a large error
 hiai_cn_recognize_modify_padv2.pb;1,32,512,1 27
 hiai_model_normalize_object_scene_ps_20200519.pb;1,224,224,3 17
-# the output of mtk_model_ckpt.pb has small value
+# The output of mtk_model_ckpt.pb has small value
 mtk_model_ckpt.pb 19
 mtk_age_gender.pb 0.5
+# The Difference of output node divided by 0 results in cumulative deviation
 mtk_model_normalize_object_scene_ps_20200519.pb;1,224,224,3 10
+# Bccumulative error of conv_batchnorm_fused op
 mtk_AADB_HADB_MBV2_model.pb;1,224,224,3 5.5
 mtk_AADB_HADB_MBV3_model.pb;1,224,224,3 4
-# the output of mtk_face_features_v1.pb has small value
+# The output of mtk_face_features_v1.pb has small value
 mtk_face_features_v1.pb 26
 model_normalize_object_scene_ps_20200519.pb;1,224,224,3 10
 hiai_AADB_HADB_MBV2_model.pb;1,224,224,3 6
@@ -39,12 +43,14 @@ hiai_cpu_face_gazing.pb 0.5
 hiai_cpu_face_emotion.pb 2
 hiai_cv_poseEstimation.pb 103
 Q_dila-small-mix-full-fineturn-390000-nopixel-nosigmoid.pb 1.5
-# the input of Q_crnn_ori_75w_slim model is between 0-255, but its outputs has small values (e-6).
+# The input of Q_crnn_ori_75w_slim model is between 0-255, but its outputs has small values (e-6).
 Q_crnn_ori_75w_slim_norm.pb 37
-# the output of Q_crnn_ori_v2 model has small values (e-4).
+# The output of Q_crnn_ori_v2 model has small values (e-4).
 Q_crnn_ori_v2_405001_notrans_nopre.pb 24
-# the input of hiai_latin models are between 0-255
+# The input of hiai_latin models are between 0-255
 hiai_latin_ocr.pb 4
 hiai_latin_ocr_1.pb 3.5
 hiai_cpu_face_headpose.pb 4
+# ml_noya_tts_melgan.pb  If the input range is adjusted to [- 1,1], the fp16 error can be reduced to 38.9512% 
+ml_noya_tts_melgan.pb;16,16,80 70
 bolt_segment.pb 2

mindspore/lite/test/models_with_multiple_inputs.cfg

@@ -31,3 +31,4 @@ add_uint8.tflite;2
 ml_Heatmap_depth_240180;2
 ml_Heatmap_depth_180240;2
 hiai_nlu_model.pb;3;1,16:1,16:1,16
+gts_object_detect_lcs.pb;1;420,630,3