A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8), EdgeTPU, CoreML.

PINTO_model_zoo

Please read the contents of the LICENSE file located directly under each folder before using the model. My model conversion scripts are released under the MIT license, but the license of the source model itself is subject to the license of the provider repository.

Contributors

Made with contrib.rocks.

TensorFlow Lite, OpenVINO, CoreML, TensorFlow.js, TF-TRT, MediaPipe, ONNX [.tflite, .h5, .pb, saved_model, tfjs, tftrt, mlmodel, .xml/.bin, .onnx]

I have been working on quantization of various models as a hobby, but I have skipped the work of making sample code to check the operation because it takes a lot of time. I welcome a pull request from volunteers to provide sample code. :smile:

[Note Jan 05, 2020] Currently, the MobileNetV3 backbone model and the Full Integer Quantization model do not return correctly.

[Note Jan 08, 2020] If you want the best performance with RaspberryPi4/3, install Ubuntu 19.10 aarch64 (64bit) instead of Raspbian armv7l (32bit). The official Tensorflow Lite is performance tuned for aarch64. On aarch64 OS, performance is about 4 times higher than on armv7l OS.

My article

List of pre-quantized models

* WQ = Weight Quantization ** OV = OpenVINO IR *** CM = CoreML **** DQ = Dynamic Range Quantization

1. Image Classification

No.	Model Name	Link	FP32	FP16	INT8	DQ	TPU	WQ	OV	CM	TFJS	TF-TRT	ONNX	Remarks
004	Efficientnet	■■■	⚫		⚫			⚫
010	Mobilenetv3	■■■	⚫		⚫			⚫
011	Mobilenetv2	■■■	⚫		⚫	⚫		⚫
016	Efficientnet-lite	■■■	⚫	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫
070	age-gender-recognition	■■■	⚫	⚫	⚫			⚫	⚫	⚫	⚫	⚫	⚫
083	Person_Reidentification	■■■	⚫	⚫	⚫			⚫	⚫	⚫	⚫	⚫	⚫	248,277,286,287,288,300
087	DeepSort	■■■	⚫	⚫	⚫			⚫	⚫	⚫		⚫	⚫
124	person-attributes-recognition-crossroad-0230	■■■	⚫	⚫	⚫			⚫	⚫	⚫	⚫	⚫	⚫
125	person-attributes-recognition-crossroad-0234	■■■	⚫	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫
126	person-attributes-recognition-crossroad-0238	■■■	⚫	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫
175	face-recognition-resnet100-arcface-onnx	■■■	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫	⚫	RGB/BGR,112x112,[1,512]
187	vehicle-attributes-recognition-barrier-0039	■■■	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	72x72
188	vehicle-attributes-recognition-barrier-0042	■■■	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	72x72
191	anti-spoof-mn3	■■■	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫		⚫	128x128
192	open-closed-eye-0001	■■■	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫		⚫	32x32
194	face_recognizer_fast	■■■	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	112x112
195	person_reid_youtu	■■■	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	256x128, ReID
199	NSFW	■■■	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	224x224
244	FINNger	■■■	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫		⚫	96x96
256	SFace	■■■	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫		⚫	112x112
257	PiCANet	■■■							⚫				⚫	BDDA,SAGE/224x224
259	Emotion_FERPlus	■■■	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫		⚫	64x64
290	AdaFace	■■■	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫		⚫	112x112
317	MobileOne	■■■											⚫	224x224
346	facial_expression_recognition_mobilefacenet	■■■	⚫	⚫	⚫	⚫		⚫					⚫	112x112
379	PP-LCNetV2	■■■	⚫	⚫									⚫	224x224
429	OSNet	■■■											⚫	256x128, ReID
430	FastReID	■■■											⚫	384x128, ReID
431	NITEC	■■■											⚫	224x224, Gaze Estimation
432	face-reidentification-retail-0095	■■■	⚫	⚫									⚫	128x128, FaceReID
451	DAN	■■■											⚫	224x224, Facial Expression
452	FairFace	■■■											⚫	224x224, Face Attribute
453	FairDAN	■■■											⚫	224x224, Face Attribute + Facial Expression
462	Gaze-LLE	■■■											⚫	448x448, Attention
474	Gaze-LLE-DINOv3	■■■											⚫	640x640,416x416,320x320, Attention
475	VSDLM	■■■											⚫	30x48, Lip motion
476	OCEC	■■■											⚫	24x40, Wink/Blink
477	PGC	■■■											⚫	32x32, Pointing
478	SC	■■■											⚫	32x24, Sitting
479	PUC	■■■											⚫	32x24, Phone Usage Classifier
480	HSC	■■■											⚫	48x48, Happy smile classifier
481	WHC	■■■											⚫	4x32x32,6x32x32,8x32x32, Waving Hand Classification
483	LVFace	■■■											⚫	Nx3x112x112, Cosine similarity
484	TransFace	■■■											⚫	Nx3x112x112, Cosine similarity
486	MWC	■■■											⚫	Nx3x48x48, Mask wearing classifier
489	Glasses-Detector	■■■											⚫	Glasses
491	SGC	■■■											⚫	Sunglasses
492	HHC	■■■											⚫	Hat
494	BPC	■■■											⚫	Background Plain classification
495	Comprehensive-Head-Classification	■■■	⚫										⚫	Comprehensive head classification
497	PPC	■■■											⚫	Binary classification to determine whether the subject is holding a smartphone
502	PersonViT	■■■											⚫	Person Re-Identification
503	CDNet	■■■											⚫	Person Re-Identification

2. 2D Object Detection

No.	Model Name	Link	FP32	FP16	INT8	TPU	DQ	WQ	OV	CM	TFJS	TF-TRT	ONNX	Remarks
002	Mobilenetv3-SSD	■■■	⚫		⚫			⚫		⚫
006	Mobilenetv2-SSDlite	■■■	⚫		⚫	⚫		⚫
008	Mask_RCNN_Inceptionv2	■■■	⚫	⚫				⚫
018	EfficientDet	■■■	⚫	⚫	⚫			⚫	⚫	⚫	⚫	⚫	⚫
023	Yolov3-nano	■■■	⚫	⚫				⚫					⚫
024	Yolov3-lite	■■■	⚫	⚫	⚫			⚫	⚫				⚫
031	Yolov4	■■■	⚫	⚫	⚫	⚫		⚫					⚫
034	SSD_Mobilenetv2_mnasfpn	■■■	⚫	⚫	⚫	⚫		⚫					⚫
038	SSDlite_MobileDet_edgetpu	■■■	⚫	⚫	⚫	⚫		⚫			⚫	⚫	⚫
039	SSDlite_MobileDet_cpu	■■■	⚫	⚫	⚫			⚫
042	Centernet	■■■	⚫	⚫	⚫			⚫	⚫	⚫	⚫	⚫	⚫
045	SSD_Mobilenetv2_oid_v4	■■■	⚫	⚫	⚫	⚫		⚫			⚫
046	Yolov4-tiny	■■■	⚫	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫
047	SpineNetMB_49	■■■	⚫	⚫	⚫			⚫					⚫	Mobile RetinaNet
051	East_Text_Detection	■■■	⚫	⚫	⚫	⚫		⚫	⚫		⚫	⚫	⚫
054	KNIFT	■■■	⚫	⚫	⚫			⚫	⚫				⚫	MediaPipe
056	TextBoxes++ with dense blocks, separable convolution and Focal Loss	■■■	⚫	⚫	⚫			⚫	⚫	⚫		⚫	⚫
058	keras-retinanet	■■■	⚫	⚫				⚫	⚫		⚫	⚫	⚫	resnet50_coco_best_v2.1.0.h5,320x320
072	NanoDet	■■■	⚫	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫	issue #274
073	RetinaNet	■■■	⚫	⚫	⚫			⚫	⚫	⚫	⚫	⚫	⚫
074	Yolact	■■■	⚫	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫
085	Yolact_Edge	■■■	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	21/10/05 new MobileNetV2(550x550)
089	DETR	■■■	⚫	⚫	⚫			⚫					⚫	256x256
103	EfficientDet_lite	■■■	⚫	⚫	⚫	⚫		⚫	⚫		⚫	⚫	⚫	lite0,lite1,lite2,lite3,lite4
116	DroNet	■■■	⚫	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫	DroNet,DroNetV3
123	YOLOR	■■■	⚫	⚫	⚫	⚫		⚫	⚫	⚫	⚫		⚫	ssss_s2d/320x320,640x640,960x960,1280x1280
132	YOLOX	■■■	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫		⚫	nano,tiny,s,m,l,x/256x320,320x320,416x416,480x640,544x960,736x1280,1088x1920
143	RAPiD	■■■	⚫	⚫	⚫			⚫	⚫				⚫	Fisheye, cepdof/habbof/mw_r, 608x608/1024x1024
145	text_detection_db	■■■	⚫	⚫	⚫			⚫	⚫	⚫	⚫	⚫	⚫	480x640
151	object_detection_mobile_object_localizer	■■■	⚫	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫	192x192
169	spaghettinet_edgetpu	■■■	⚫	⚫	⚫	⚫	⚫	⚫	⚫		⚫	⚫	⚫	320x320,S/M/L
174	PP-PicoDet	■■■	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫	⚫	S/M/L,320x320/416x416/640x640
178	vehicle-detection-0200	■■■	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	256x256,PriorBoxClustered->ndarray(0.npy)
179	person-detection-0202	■■■	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	512x512,PriorBoxClustered->ndarray(0.npy)
183	pedestrian-detection-adas-0002	■■■	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	384x672,PriorBox->ndarray(0.npy)
184	pedestrian-and-vehicle-detector-adas-0001	■■■	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	384x672,PriorBox->ndarray(0.npy)
185	person-vehicle-bike-detection-crossroad-0078	■■■	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫	⚫	1024x1024,PriorBoxClustered->ndarray(0.npy)
186	person-vehicle-bike-detection-crossroad-1016	■■■	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	512x512,PriorBoxClustered->ndarray(0.npy)
189	vehicle-license-plate-detection-barrier-0106	■■■	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	300x300,PriorBoxClustered->ndarray(0.npy)
190	person-detection-asl-0001	■■■	⚫	⚫	⚫		⚫	⚫	⚫				⚫	320x320
197	yolact-resnet50-fpn	■■■	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫	⚫	RGB,550x550
198	YOLOF	■■■	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫	⚫	BGR/RGB,608x608
221	YOLACT-PyTorch	■■■	⚫	⚫	⚫		⚫	⚫	⚫		⚫	⚫	⚫	180x320,240x320,320x480,480x640,544x544,720x1280
226	CascadeTableNet	■■■	⚫	⚫			⚫	⚫	⚫				⚫	General,320x320 only
262	ByteTrack	■■■											⚫	YOLOX/nano,tiny,s,m,l,x,mot17,ablation/128x320,192x320,192x448,192x640,256x320,256x448,256x640,384x640,512x1280,736x1280
264	object_localization_network	■■■											⚫	180x320,240x320,270x480,360x480,360x480,360x640,480x640,720x1280
307	YOLOv7	■■■	⚫	⚫	⚫		⚫	⚫	⚫		⚫		⚫	YOLOv7,YOLOv7-tiny
308	FastestDet	■■■	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫		⚫	180x320,256x320,320x480,352x352,352x640,480x640,736x1280
329	YOLOX-PAI	■■■											⚫
332	CrowdDet	■■■											⚫
334	DAMO-YOLO	■■■											⚫
336	PP-YOLOE-Plus	■■■											⚫
337	FreeYOLO	■■■											⚫
341	YOLOv6	■■■	⚫	⚫	⚫		⚫	⚫					⚫
356	EdgeYOLO	■■■											⚫
376	RT-DETR	■■■											⚫	ResNet50,ResNet101,HgNetv2-L,HgNetv2-X
386	naruto_handsign_detection	■■■	⚫	⚫	⚫		⚫						⚫
422	Gold-YOLO-Head-Hand	■■■											⚫	Head,Hand
424	Gold-YOLO-Body	■■■											⚫	Body
425	Gold-YOLO-Body-Head-Hand	■■■											⚫	Body,Head,Hand
426	YOLOX-Body-Head-Hand	■■■	⚫	⚫	⚫								⚫	Body,Head,Hand, tflite float16 XNNPACK boost (ARMv8.2)
434	YOLOX-Body-Head-Hand-Face	■■■											⚫	Body,Head,Hand,Face
441	YOLOX-Body-Head-Hand-Face-Dist	■■■											⚫	Body,Head,Hand,Face,Complex Distorted
442	YOLOX-Body-Head-Face-HandLR-Dist	■■■											⚫	Body,Head,Hands,Left-Hand,Right-Hand,Face,Complex Distorted
444	YOLOX-Foot-Dist	■■■											⚫	Foot,Complex Distorted
445	YOLOX-Body-Head-Face-HandLR-Foot-Dist	■■■											⚫	Body,Head,Face,Hands,Left-Hand,Right-Hand,Foot,Complex Distorted
446	YOLOX-Body-With-Wheelchair	■■■											⚫	Body with WheelChair
447	YOLOX-Wholebody-with-Wheelchair	■■■											⚫	Wholebody with WheelChair
448	YOLOX-Eye-Nose-Mouth-Ear	■■■											⚫
449	YOLOX-WholeBody12	■■■											⚫	Body,BodyWithWheelchair,Head,Face,Eye,Nose,Mouth,Ear,Hand,Hand-Left,Hand-Right,Foot
450	YOLOv9-Wholebody-with-Wheelchair	■■■											⚫	Wholebody with WheelChair
454	YOLOv9-Wholebody13	■■■											⚫	Body,BodyWithWheelchair,BodyWithCrutches,Head,Face,Eye,Nose,Mouth,Ear,Hand,Hand-Left,Hand-Right,Foot
455	YOLOv9-Gender	■■■											⚫	Body,Male,Female
456	YOLOv9-Wholebody15	■■■											⚫	Body,Male,Female,BodyWithWheelchair,BodyWithCrutches,Head,Face,Eye,Nose,Mouth,Ear,Hand,Hand-Left,Hand-Right,Foot
457	YOLOv9-Wholebody17	■■■											⚫	Body,Male,Adult,Child,Female,BodyWithWheelchair,BodyWithCrutches,Head,Face,Eye,Nose,Mouth,Ear,Hand,Hand-Left,Hand-Right,Foot
458	YOLOv9-Discrete-HeadPose-Yaw	■■■											⚫	Head,Front,Right-Front,Right-Side,Right-Back,Back,Left-Back,Left-Side,Left-Front
459	YOLOv9-Wholebody25	■■■											⚫	Body,Adult,Child,Male,Female,Body_with_Wheelchair,Body_with_Crutches,Head,Front,Right_Front,Right_Side,Right_Back,Back,Left_Back,Left_Side,Left_Front,Face,Eye,Nose,Mouth,Ear,Hand,Hand_Left,Hand_Right,Foot
460	RT-DETRv2-Wholebody25	■■■											⚫	Body,Adult,Child,Male,Female,Body_with_Wheelchair,Body_with_Crutches,Head,Front,Right_Front,Right_Side,Right_Back,Back,Left_Back,Left_Side,Left_Front,Face,Eye,Nose,Mouth,Ear,Hand,Hand_Left,Hand_Right,Foot
461	YOLOv9-Phone	■■■											⚫	Phone
463	YOLOv9-Shoulder-Elbow-Knee	■■■											⚫	Shoulder,Elbow,Knee
464	YOLOv9-Wholebody28	■■■											⚫	Body,Adult,Child,Male,Female,Body_with_Wheelchair,Body_with_Crutches,Head,Front,Right_Front,Right_Side,Right_Back,Back,Left_Back,Left_Side,Left_Front,Face,Eye,Nose,Mouth,Ear,Shoulder,Elbow,Hand,Hand_Left,Hand_Right,Knee,Foot
465	DEIM-Wholebody28	■■■											⚫	Body,Adult,Child,Male,Female,Body_with_Wheelchair,Body_with_Crutches,Head,Front,Right_Front,Right_Side,Right_Back,Back,Left_Back,Left_Side,Left_Front,Face,Eye,Nose,Mouth,Ear,Shoulder,Elbow,Hand,Hand_Left,Hand_Right,Knee,Foot
468	YOLOv9-Wholebody28-Refine	■■■											⚫	Body,Adult,Child,Male,Female,Body_with_Wheelchair,Body_with_Crutches,Head,Front,Right_Front,Right_Side,Right_Back,Back,Left_Back,Left_Side,Left_Front,Face,Eye,Nose,Mouth,Ear,Shoulder,Elbow,Hand,Hand_Left,Hand_Right,Knee,Foot
471	YOLO-Wholebody34	■■■											⚫	body,adult,child,male,female,body_with_wheelchair,body_with_crutches,head,front,right-front,right-side,right-back,back,left-back,left-side,left-front,face,eye,nose,mouth,ear,collarbone,shoulder,solar_plexus,elbow,wrist,hand,hand_left,hand_right,abdomen,hip_joint,knee,ankle,foot
472	DEIMv2-Wholebody34	■■■											⚫	body,adult,child,male,female,body_with_wheelchair,body_with_crutches,head,front,right-front,right-side,right-back,back,left-back,left-side,left-front,face,eye,nose,mouth,ear,collarbone,shoulder,solar_plexus,elbow,wrist,hand,hand_left,hand_right,abdomen,hip_joint,knee,ankle,foot
473	HISDF	■■■											⚫	Object Detection x Depth Estimation x Pose Estimation x Instance Segmentation x Binary Segmentation
482	UHD	■■■											⚫	64x64, Object Detection, Human Detection
485	DEIMv2-Wholebody40	■■■											⚫	40 classes
489	489_Glasses-Detector	■■■											⚫	glasses

3. 3D Object Detection

No.	Model Name	Link	FP32	FP16	INT8	TPU	DQ	WQ	OV	CM	TFJS	TF-TRT	ONNX	Remarks
036	Objectron	■■■	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	MediaPipe/camera,chair,chair_1stage,cup,sneakers,sneakers_1stage,ssd_mobilenetv2_oidv4_fp16
063	3D BoundingBox estimation for autonomous driving	■■■	⚫	⚫	⚫			⚫	⚫	⚫	⚫	⚫	⚫	YouTube
107	SFA3D	■■■	⚫	⚫	⚫			⚫	⚫	⚫	⚫	⚫	⚫
263	EgoNet	■■■	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫		⚫
321	DID-M3D	■■■											⚫
363	YOLO-6D-Pose	■■■	⚫								⚫		⚫	Texas Instruments ver, PINTO Special ver

4. 2D/3D Face Detection

No.	Model Name	Link	FP32	FP16	INT8	TPU	DQ	WQ	OV	CM	TFJS	TF-TRT	ONNX	Remarks
025	Head_Pose_Estimation	■■■	⚫	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫
030	BlazeFace	■■■	⚫	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫	MediaPipe
032	FaceMesh	■■■	⚫	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫	MediaPipe
040	DSFD_vgg	■■■	⚫	⚫				⚫
041	DBFace	■■■	⚫	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫	MobileNetV2/V3, 320x320,480x640,640x960,800x1280
043	Face_Landmark	■■■	⚫	⚫	⚫			⚫	⚫	⚫	⚫	⚫	⚫
049	Iris_Landmark	■■■	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	MediaPipe
095	CenterFace	■■■	⚫	⚫	⚫			⚫	⚫	⚫	⚫	⚫	⚫
096	RetinaFace	■■■	⚫	⚫	⚫			⚫	⚫	⚫	⚫	⚫	⚫
106	WHENet	■■■	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫		⚫	Real-time Fine-Grained Estimation for Wide Range Head Pose
129	SCRFD	■■■	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫	⚫	All types
134	head-pose-estimation-adas-0001	■■■	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	60x60
144	YuNet	■■■	⚫	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫	120x160
227	face-detection-adas-0001	■■■	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	384x672,PriorBox->ndarray(0.npy)
250	Face-Mask-Detection	■■■	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫		⚫	PriorBox->ndarray(0.npy)
282	face_landmark_with_attention	■■■	⚫	⚫	⚫		⚫	⚫	⚫		⚫		⚫	MediaPipe,192x192
289	face-detection-0100	■■■	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫		⚫	256x256,PriorBoxClustered->ndarray(0.npy)
293	Lightweight-Head-Pose-Estimation	■■■	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫		⚫	HeadPose, 224x224
300	6DRepNet	■■■	⚫	⚫	⚫		⚫	⚫	⚫		⚫		⚫	6D HeadPose, 224x224
301	YOLOv4_Face	■■■											⚫	480x640
302	SLPT	■■■											⚫	decoder=6/12,256x256
303	FAN	■■■	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫		⚫	Face Alignment,128x128/256x256
304	SynergyNet	■■■											⚫	6D HeadPose,224x224
305	DMHead	■■■											⚫	6D HeadPose,Multi-Model-Fused,224x224,PINTO's custom models
311	HHP-Net	■■■	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫		⚫	6D HeadPose,No-LICENSE
319	ACR-Loss	■■■	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫		⚫	Face Alignment
322	YOLOv7_Head	■■■											⚫	PINTO's custom models
383	DirectMHP	■■■	⚫	⚫									⚫
387	YuNetV2	■■■	⚫	⚫	⚫		⚫						⚫	640x640
390	BlendshapeV2	■■■	⚫	⚫									⚫	1x146x2,Nx146x2,MediaPipe
399	RetinaFace_MobileNetv2	■■■											⚫
410	FaceMeshV2	■■■	⚫	⚫	⚫		⚫		⚫				⚫	MediaPipe
414	STAR	■■■	⚫	⚫	⚫		⚫		⚫				⚫
421	Gold-YOLO-Head	■■■											⚫	Head (not Face)
423	6DRepNet360	■■■											⚫	6D HeadPose, FullRange, 224x224
433	FaceBoxes.PyTorch	■■■											⚫	2D Face
435	MobileFaceNet	■■■											⚫	Face Alignment,112x112
436	Peppa_Pig_Face_Landmark	■■■											⚫	Face Alignment,128x128,256x256
437	PIPNet	■■■											⚫	Face Alignment,256x256
443	Opal23_HeadPose	■■■											⚫	6D HeadPose, FullRange, 128x128
504	HRFFA	■■■											⚫	Face Alignment
505	YawNet	■■■											⚫	Head Pose Estimation
506	HFHPE	■■■											⚫	6D Head Pose Estimation

5. 2D/3D Hand Detection

No.	Model Name	Link	FP32	FP16	INT8	TPU	DQ	WQ	OV	CM	TFJS	TF-TRT	ONNX	Remarks
027	Minimal-Hand	■■■	⚫	⚫	⚫			⚫		⚫	⚫	⚫	⚫
033	Hand_Detection_and_Tracking	■■■	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	MediaPipe
094	hand_recrop	■■■	⚫	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫	MediaPipe
403	trt_pose_hand	■■■											⚫	2D
420	Gold-YOLO-Hand	■■■											⚫	2D
438	PeCLR	■■■											⚫	2D+3D

6. 2D/3D Human/Animal Pose Estimation

No.	Model Name	Link	FP32	FP16	INT8	TPU	DQ	WQ	OV	CM	TFJS	TF-TRT	ONNX	Remarks
003	Posenet	■■■	⚫	⚫	⚫	⚫		⚫	⚫
007	Mobilenetv2_Pose_Estimation	■■■	⚫	⚫	⚫	⚫		⚫	⚫		⚫	⚫
029	Human_Pose_Estimation_3D	■■■	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	RGB,180x320,240x320,360x640,480x640,720x1280
053	BlazePose	■■■	⚫	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫	MediaPipe
065	ThreeDPoseUnityBarracuda	■■■	⚫	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫	YouTube
080	tf_pose_estimation	■■■	⚫	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫
084	EfficientPose	■■■	⚫	⚫	⚫			⚫	⚫	⚫	⚫	⚫	⚫	SinglePose
088	Mobilenetv3_Pose_Estimation	■■■	⚫	⚫	⚫			⚫	⚫	⚫	⚫	⚫	⚫
115	MoveNet	■■■	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫	⚫	lightning,thunder
137	MoveNet_MultiPose	■■■	⚫	⚫	⚫			⚫	⚫	⚫	⚫	⚫	⚫	lightning,192x192,192x256,256x256,256x320,320x320,480x640,720x1280,1280x1920
156	MobileHumanPose	■■■	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	⚫	3D
157	3DMPPE_POSENET	■■■	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫	⚫	3D,192x192/256x256/320x320/416x416/480x640/512x512
265	PoseAug	■■■	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫		⚫	2D->3D/GCN,MLP,STGCN,VideoPose/Nx16x2
268	Lite-HRNet	■■■	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫		⚫	COCO,MPII/Top-Down
269	Higher-HRNet	■■■	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫		⚫	192x320,256x320,320x480,384x640,480x640,512x512,576x960,736x1280/Bottom-Up
271	HRNet	■■■											⚫	COCO,MPII/Top-Down
333	E2Pose	■■■	⚫	⚫	⚫		⚫						⚫	COCO/CrowdPose,End-to-End
350	P-STMO	■■■											⚫	2D->3D,in_the_wild
355	MHFormer	■■■	⚫	⚫									⚫	2D->3D
365	HTNet	■■■	⚫	⚫									⚫	2D->3D
392	STCFormer	■■■	⚫	⚫									⚫	2D->3D
393	RTMPose_WholeBody	■■■	⚫	⚫	⚫		⚫						⚫	2D
394	RTMPose_Animal	■■■	⚫	⚫	⚫		⚫						⚫	2D
402	trt_pose	■■■											⚫	2D
412	pytorch_cpn	■■■	⚫	⚫									⚫	2D
427	RTMPose_Hand	■■■											⚫	2D
440	ViTPose	■■■											⚫	2D

7. Depth Estimation from Monocular/Stereo Images

No.	Model Name	Link	FP32	FP16	INT8	TPU	DQ	WQ	OV	CM	TFJS	TF-TRT	ONNX	Remarks
009	Multi-Scale Local Planar Guidance for Monocular Depth Estimation	■■■	⚫
014	tf-monodepth2	■■■	⚫	⚫	⚫			⚫	⚫	⚫		⚫	⚫
028	struct2depth	■■■	⚫	⚫				⚫					⚫
064	Dense Depth	■■■	⚫	⚫	⚫			⚫	⚫	⚫	⚫	⚫	⚫
066	Footprints	■■■	⚫	⚫	⚫			⚫	⚫	⚫	⚫	⚫	⚫
067	MiDaS	■■■	⚫	⚫	⚫			⚫	⚫	⚫	⚫	⚫	⚫
081	MiDaS v2	■■■	⚫	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫
135	CoEx	■■■							⚫				⚫	WIP, onnx/OpenVINO only
142	HITNET	■■■	⚫	⚫				⚫					⚫	WIP issue1,issue2,flyingthings_finalpass_xl/eth3d/middlebury_d400,120x160/240x320/256x256/480x640/720x1280
146	FastDepth	■■■	⚫	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫	128x160,224x224,256x256,256x320,320x320,480x640,512x512,768x1280
147	PackNet-SfM	■■■	⚫	⚫	⚫			⚫	⚫	⚫	⚫	⚫	⚫	ddad/kitti,Convert all ResNet18 backbones only
148	LapDepth	■■■	⚫	⚫	⚫			⚫	⚫	⚫	⚫	⚫	⚫	kitti/nyu,192x320/256x320/368x640/480x640/720x1280
149	depth_estimation	■■■	⚫	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫	nyu,180x320/240x320/360x640/480x640/720x1280
150	MobileStereoNet	■■■												WIP. Conversion script only.
153	MegaDepth	■■■	⚫	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫	192x256,384x512
158	HR-Depth	■■■	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫	⚫
159	EPCDepth	■■■	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫	⚫
160	msg_chn_wacv20	■■■	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫		⚫	192x320,240x320,256x256,352x480,368x480,368x640,480x640,720x1280,1280x1920
162	PyDNet	■■■	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫	⚫
164	MADNet	■■■	⚫	⚫				⚫	⚫	⚫	⚫	⚫	⚫	Real-time-self-adaptive-deep-stereo (perform only inference mode, no-backprop, kitti)
165	RealtimeStereo	■■■	⚫	⚫			⚫	⚫	⚫		⚫	⚫	⚫	180x320,216x384,240x320,270x480,360x480,360x640,480x640,720x1280
166	Insta-DM	■■■	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫	⚫	192x320,256x320,256x832,384x640,480x640,736x1280
167	DPT	■■■	⚫	⚫			⚫	⚫	⚫	⚫	⚫	⚫	⚫	dpt-hybrid,480x640,ViT,ONNX 96x128/256x320/384x480/480x640
173	MVDepthNet	■■■							⚫				⚫	256x320
202	stereoDNN	■■■	⚫	⚫			⚫	⚫	⚫	⚫		⚫	⚫	NVSmall_321x1025,NVTiny_161x513,ResNet18_321x1025,ResNet18_2d_257x513
203	SRHNet	■■■											⚫	finetune2_kitti/sceneflow,maxdisp192,320x480/480x640
210	SC_Depth_pl	■■■	⚫	⚫	⚫		⚫	⚫	⚫	⚫	⚫	⚫	⚫	kitti/nyu,320x320,320x480,480x640,640x800
211	Lac-GwcNet	■■■											⚫	kitti,240x320,320x480,480x640,720x1280
219	StereoNet	■■■	⚫	⚫	⚫		⚫	⚫	⚫			⚫	⚫	Left/180x320,240x320,320x480,360x640,480x640
235	W-Stereo-Disp	■■■											⚫	Kitti,Sceneflow/320x480,384x576,480x640
236	A-TVSNet	■■■	⚫	⚫			⚫	⚫					⚫	Stereo only/192x320,256x320,320x480,480x640
239	CasStereoNet	■■■											⚫	Stereo KITTI only/256x320,384x480,480x640,736x1280
245	GLPDepth	■■■							⚫				⚫	Kitti,NYU/192x320,320x480,384x640,480x640,736x1280,non-commercial use only
258	TinyHITNet	■■■							⚫				⚫	180x320,240x320,300x400,360x640,384x512,480x640,720x960,720x1280
266	ACVNet	■■■							⚫				⚫	sceneflow,kitti/240x320,320x480,384x640,480x640,544x960,720x1280
280	GASDA	■■■											⚫	No-LICENSE
284	CREStereo	■■■											⚫	ITER2,ITER5,ITER10,ITER20/240x320,320x480,360x640,480x640,480x640,720x1280
292	Graft-PSMNet	■■■											⚫	192x320,240x320,320x480,368x640,480x640,720x1280
294	FSRE-Depth	■■■							⚫				⚫	192x320,256x320,320x480,368x640,480x640,736x1280
296	MGNet	■■■	⚫	⚫	⚫		⚫	⚫	⚫		⚫		⚫	240x320,360x480,360x640,360x1280,480x640,720x1280
312	NeWCRFs	■■■											⚫	384x384,384x576,384x768,384x960,576x768,768x1344