Awesome
CoreML-Models
Converted Core ML Model Zoo.
<img width="1280" src="https://user-images.githubusercontent.com/23278992/147420041-fdeb1fbb-7e93-41c6-84d6-80d7c1c45200.jpeg">Core ML is a machine learning framework by Apple. If you are iOS developer, you can easly use machine learning models in your Xcode project.
How to use
Take a look this model zoo, and if you found the CoreML model you want, download the model from google drive link and bundle it in your project. Or if the model have sample project link, try it and see how to use the model in the project. You are free to do or not.
If you like this repository, please give me a star so I can do my best.
Section Link
-
Stable Diffusion :text2image
How to get the model
You can get the model converted to CoreML format from the link of Google drive. See the section below for how to use it in Xcode. The license for each model conforms to the license for the original project.
Image Classifier
Efficientnet
<img width="400" alt="スクリーンショット 2021-12-27 6 34 43" src="https://user-images.githubusercontent.com/23278992/147420587-108b87f8-7996-4288-905a-ad53f9142221.png">Google Drive Link | Size | Dataset | Original Project | License |
---|---|---|---|---|
Efficientnetb0 | 22.7 MB | ImageNet | TensorFlowHub | Apache2.0 |
Efficientnetv2
<img width="400" alt="スクリーンショット 2021-12-31 4 30 22" src="https://user-images.githubusercontent.com/23278992/147782567-bbf26186-8c84-4073-8df4-b08e06d4e791.png">Google Drive Link | Size | Dataset | Original Project | License | Year |
---|---|---|---|---|---|
Efficientnetv2 | 85.8 MB | ImageNet | Google/autoML | Apache2.0 | 2021 |
VisionTransformer
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.
<img width="400" alt="スクリーンショット 2022-01-07 10 37 05" src="https://user-images.githubusercontent.com/23278992/148482246-64269fb4-fda4-4bd5-b219-5bf860fd77e7.png">Google Drive Link | Size | Dataset | Original Project | License | Year |
---|---|---|---|---|---|
VisionTransformer-B16 | 347.5 MB | ImageNet | google-research/vision_transformer | Apache2.0 | 2021 |
Conformer
Local Features Coupling Global Representations for Visual Recognition.
<img width="400" alt="スクリーンショット 2022-01-07 11 34 33" src="https://user-images.githubusercontent.com/23278992/148482144-2d5bb7e8-ed67-4146-9f9d-c95fe94735d3.png">Google Drive Link | Size | Dataset | Original Project | License | Year |
---|---|---|---|---|---|
Conformer-tiny-p16 | 94.1 MB | ImageNet | pengzhiliang/Conformer | Apache2.0 | 2021 |
DeiT
Data-efficient Image Transformers
<img width="400" alt="スクリーンショット 2022-01-07 11 50 25" src="https://user-images.githubusercontent.com/23278992/148484220-38494287-49b4-4992-9ceb-9dc7b75a250e.png">Google Drive Link | Size | Dataset | Original Project | License | Year |
---|---|---|---|---|---|
DeiT-base384 | 350.5 MB | ImageNet | facebookresearch/deit | Apache2.0 | 2021 |
RepVGG
Making VGG-style ConvNets Great Again
<img width="400" alt="スクリーンショット 2022-01-08 5 00 53" src="https://user-images.githubusercontent.com/23278992/148600326-69dd9666-2709-4318-914b-30db8c294fd3.png">Google Drive Link | Size | Dataset | Original Project | License | Year |
---|---|---|---|---|---|
RepVGG-A0 | 33.3 MB | ImageNet | DingXiaoH/RepVGG | MIT | 2021 |
RegNet
Designing Network Design Spaces
<img width="400" alt="スクリーンショット 2022-02-23 7 38 23" src="https://user-images.githubusercontent.com/23278992/155233183-edf61ebe-922c-4b63-8a5e-7ef6c9f7eaa8.png">Google Drive Link | Size | Dataset | Original Project | License | Year |
---|---|---|---|---|---|
regnet_y_400mf | 16.5 MB | ImageNet | TORCHVISION.MODELS | MIT | 2020 |
MobileViTv2
CVNets: A library for training computer vision networks
<img width="400" alt="スクリーンショット 2022-02-23 7 38 23" src="https://user-images.githubusercontent.com/23278992/225600794-a0a4dc00-cc67-4614-82ed-3ed8633cf03e.png">Google Drive Link | Size | Dataset | Original Project | License | Year | Conversion Script |
---|---|---|---|---|---|---|
MobileViTv2 | 18.8 MB | ImageNet | apple/ml-cvnets | apple | 2022 |
Object Detection
YOLOv5s
<img width="400" alt="スクリーンショット 2021-12-29 6 17 08" src="https://user-images.githubusercontent.com/23278992/147608051-be2ff345-22e8-4f82-83ed-7cc41ce4084d.png">Google Drive Link | Size | Output | Original Project | License | Note | Sample Project |
---|---|---|---|---|---|---|
YOLOv5s | 29.3MB | Confidence(MultiArray (Double 0 × 80)), Coordinates (MultiArray (Double 0 × 4)) | ultralytics/yolov5 | GNU | Non Maximum Suppression has been added. | CoreML-YOLOv5 |
YOLOv7
<img width="400" alt="スクリーンショット 2021-12-29 6 17 08" src="https://user-images.githubusercontent.com/23278992/178128011-e0056777-0c2a-495b-b132-7741cc693077.png">Google Drive Link | Size | Output | Original Project | License | Note | Sample Project | Conversion Script |
---|---|---|---|---|---|---|---|
YOLOv7 | 147.9MB | Confidence(MultiArray (Double 0 × 80)), Coordinates (MultiArray (Double 0 × 4)) | WongKinYiu/yolov7 | GNU | Non Maximum Suppression has been added. | CoreML-YOLOv5 |
YOLOv8
<img width="400" alt="スクリーンショット 2021-12-29 6 17 08" src="https://user-images.githubusercontent.com/23278992/211807010-d48854b3-beb0-46a8-bd99-cbb9351529b0.png">Google Drive Link | Size | Output | Original Project | License | Note | Sample Project |
---|---|---|---|---|---|---|
YOLOv8s | 45.1MB | Confidence(MultiArray (Double 0 × 80)), Coordinates (MultiArray (Double 0 × 4)) | ultralytics/ultralytics | GNU | Non Maximum Suppression has been added. | CoreML-YOLOv5 |
Segmentation
U2Net
<img width="400" src="https://camo.qiitausercontent.com/a8e89c72c0950db66d63415b9010d203aae22617/68747470733a2f2f71696974612d696d6167652d73746f72652e73332e61702d6e6f727468656173742d312e616d617a6f6e6177732e636f6d2f302f3233353235392f36303037393162322d633534332d613537652d303639622d3863663130373932643662392e6a706567"> <img width="400" src="https://camo.qiitausercontent.com/4f502487cd9e9e02d150ad63b33683a1446e7516/68747470733a2f2f71696974612d696d6167652d73746f72652e73332e61702d6e6f727468656173742d312e616d617a6f6e6177732e636f6d2f302f3233353235392f39636532633237612d643134322d663136352d343365662d6532373966646337386333382e706e67">
Google Drive Link | Size | Output | Original Project | License |
---|---|---|---|---|
U2Net | 175.9 MB | Image(GRAYSCALE 320 × 320) | xuebinqin/U-2-Net | Apache |
U2Netp | 4.6 MB | Image(GRAYSCALE 320 × 320) | xuebinqin/U-2-Net | Apache |
IS-Net
<img width="400" src="https://user-images.githubusercontent.com/23278992/179818731-b919c8a2-f5c9-4a80-8666-e3034d1e86f0.jpg"> <img width="400" src="https://user-images.githubusercontent.com/23278992/179818740-38336aec-c9c5-4471-b529-ae45286062b5.JPG"> <img width="400" src="https://user-images.githubusercontent.com/23278992/186722092-3b8ed1a1-4a03-4357-9bfd-9ec213e7d87d.jpeg"> <img width="400" src="https://user-images.githubusercontent.com/23278992/186791654-42b4ba54-f06f-43d3-805b-5bb89e5df272.JPG">
Google Drive Link | Size | Output | Original Project | License | Year | Conversion Script |
---|---|---|---|---|---|---|
IS-Net | 176.1 MB | Image(GRAYSCALE 1024 × 1024) | xuebinqin/DIS | Apache | 2022 | |
IS-Net-General-Use | 176.1 MB | Image(GRAYSCALE 1024 × 1024) | xuebinqin/DIS | Apache | 2022 |
RMBG1.4
RMBG1.4 - The IS-Net enhanced with our unique training scheme and proprietary dataset.
<img src="https://github.com/john-rocky/PersonSegmentationSampler/assets/23278992/2a91ec10-fe94-43be-aedc-283e71fa9a1e" width=400> <img src="https://github.com/john-rocky/PersonSegmentationSampler/assets/23278992/04af501d-996d-48f4-b008-f0076dcbc117" width=400>
Google Drive Link | Size | Output | Original Project | License | year | Conversion Script |
---|---|---|---|---|---|---|
RMBG.mlpackage/RMBG.mlmodel | 176 MB | Image(GrayScale 1024x1024) | briaai/RMBG-1.4 | Creative Commons | 2024 |
face-Parsing
<img src="https://user-images.githubusercontent.com/23278992/147860040-14a7e022-5490-4e51-98cd-cd421066dd8c.png" width=400> <img src="https://user-images.githubusercontent.com/23278992/147860042-d27f37b0-227b-45ab-8d76-f6c6f2f5b3a4.png" width=400>
Google Drive Link | Size | Output | Original Project | License | Sample Project |
---|---|---|---|---|---|
face-Parsing | 53.2 MB | MultiArray(1 x 512 × 512) | zllrunning/face-parsing.PyTorch | MIT | CoreML-face-parsing |
Segformer
Simple and Efficient Design for Semantic Segmentation with Transformers
<img src="https://user-images.githubusercontent.com/23278992/148621010-5ecf6b90-c501-4cf8-91e1-446850030265.png" width=400> <img src="https://user-images.githubusercontent.com/23278992/148621013-44d9cd29-ef3c-4250-bbd9-4e4093385a54.JPG" width=400>
Google Drive Link | Size | Output | Original Project | License | year |
---|---|---|---|---|---|
SegFormer_mit-b0_1024x1024_cityscapes | 14.9 MB | MultiArray(512 × 1024) | NVlabs/SegFormer | NVIDIA | 2021 |
BiSeNetV2
Bilateral Network with Guided Aggregation for Real-time Semantic Segmentation
<img src="https://user-images.githubusercontent.com/23278992/148663182-c1f3b9dd-8db4-49be-bf92-97a898a8b477.jpg" width=400> <img src="https://user-images.githubusercontent.com/23278992/148663183-327dc684-342d-43f1-a8d8-ebf817c91bdd.JPG" width=400>
Google Drive Link | Size | Output | Original Project | License | year |
---|---|---|---|---|---|
BiSeNetV2_1024x1024_cityscapes | 12.8 MB | MultiArray | ycszen/BiSeNet | Apache2.0 | 2021 |
DNL
Disentangled Non-Local Neural Networks
<img src="https://user-images.githubusercontent.com/23278992/150061280-23a1de7c-2e12-41d2-9056-7c4b375193a6.jpg" width=400> <img src="https://user-images.githubusercontent.com/23278992/150061290-eed50b79-f5c0-4fa4-b5bf-728b9029f34c.png" width=400>
Google Drive Link | Size | Output | Dataset | Original Project | License | year |
---|---|---|---|---|---|---|
dnl_r50-d8_512x512_80k_ade20k | 190.8 MB | MultiArray[512x512] | ADE20K | yinmh17/DNL-Semantic-Segmentation | Apache2.0 | 2020 |
ISANet
Interlaced Sparse Self-Attention for Semantic Segmentation
<img src="https://user-images.githubusercontent.com/23278992/150234575-7dcb8521-4ebd-46aa-bd19-4c1036b514dc.jpg" width=400> <img src="https://user-images.githubusercontent.com/23278992/150234561-41478d2a-b411-48df-9980-8553c381e530.png" width=400>
Google Drive Link | Size | Output | Dataset | Original Project | License | year |
---|---|---|---|---|---|---|
isanet_r50-d8_512x512_80k_ade20k | 141.5 MB | MultiArray[512x512] | ADE20K | openseg-group/openseg.pytorch | MIT | ArXiv'2019/IJCV'2021 |
FastFCN
Rethinking Dilated Convolution in the Backbone for Semantic Segmentation
<img src="https://user-images.githubusercontent.com/23278992/150237380-3b8522e6-e310-436e-b5c3-60b7ff8cb606.jpg" width=400> <img src="https://user-images.githubusercontent.com/23278992/150237372-1d17f4e2-cf1b-49f0-82b8-d9e6644ff465.png" width=400>
Google Drive Link | Size | Output | Dataset | Original Project | License | year |
---|---|---|---|---|---|---|
fastfcn_r50-d32_jpu_aspp_512x512_80k_ade20k | 326.2 MB | MultiArray[512x512] | ADE20K | wuhuikai/FastFCN | MIT | ArXiv'2019 |
GCNet
Non-local Networks Meet Squeeze-Excitation Networks and Beyond
<img src="https://user-images.githubusercontent.com/23278992/150239404-9d6438ec-cee5-44b9-9179-436ac5ceaab2.jpg" width=400> <img src="https://user-images.githubusercontent.com/23278992/150239421-cceaae77-eb6b-468d-a069-72750fc6b0f4.png" width=400>
Google Drive Link | Size | Output | Dataset | Original Project | License | year |
---|---|---|---|---|---|---|
gcnet_r50-d8_512x512_20k_voc12aug | 189 MB | MultiArray[512x512] | PascalVOC | xvjiarui/GCNet | Apache License 2.0 | ICCVW'2019/TPAMI'2020 |
DANet
Dual Attention Network for Scene Segmentation(CVPR2019)
<img src="https://user-images.githubusercontent.com/23278992/150419837-980a0e0f-6333-4853-b638-6e6854e093e3.jpg" width=400> <img src="https://user-images.githubusercontent.com/23278992/150419740-052fca9b-0519-440c-bffd-5abc7a5ac240.png" width=400>
Google Drive Link | Size | Output | Dataset | Original Project | License | year |
---|---|---|---|---|---|---|
danet_r50-d8_512x1024_40k_cityscapes | 189.7 MB | MultiArray[512x1024] | CityScapes | junfu1115/DANet | MIT | CVPR2019 |
Semantic-FPN
Panoptic Feature Pyramid Networks
<img src="https://user-images.githubusercontent.com/23278992/150614015-6b712113-6b8f-484e-88dc-124b76229153.jpg" width=400> <img src="https://user-images.githubusercontent.com/23278992/150614022-590eb6fa-075f-4ff7-8ad5-b9d502b8763b.png" width=400>
Google Drive Link | Size | Output | Dataset | Original Project | License | year |
---|---|---|---|---|---|---|
fpn_r50_512x1024_80k_cityscapes | 108.6 MB | MultiArray[512x1024] | CityScapes | facebookresearch/detectron2 | Apache License 2.0 | 2019 |
cloths_segmentation
Code for binary segmentation of various cloths.
<img src="https://user-images.githubusercontent.com/23278992/154873792-54c12be0-d446-4789-bf00-bb89cab5a566.jpg" width=400> <img src="https://user-images.githubusercontent.com/23278992/154873786-2b90e0d9-dd86-4397-8977-ea1464ca2f75.JPG" width=400>
Google Drive Link | Size | Output | Dataset | Original Project | License | year |
---|---|---|---|---|---|---|
clothSegmentation | 50.1 MB | Image(GrayScale 640x960) | fashion-2019-FGVC6 | facebookresearch/detectron2 | MIT | 2020 |
easyportrait
EasyPortrait - Face Parsing and Portrait Segmentation Dataset.
<img src="https://github.com/john-rocky/CoreML-Models/assets/23278992/6ab8ed6a-2de7-43fd-bb84-2fb77286bd6c" width=400> <img src="https://github.com/john-rocky/CoreML-Models/assets/23278992/a0b8e435-d04e-4a88-940b-bd5fb45cbc15" width=400>
Google Drive Link | Size | Output | Original Project | License | year | Swift sample | Conversion Script |
---|---|---|---|---|---|---|---|
easyportrait-segformer512-fp | 7.6 MB | Image(GrayScale 512x512) * 9 | hukenovs/easyportrait | Creative Commons | 2023 | easyportrait-coreml |
Super Resolution
Real ESRGAN
<img width="400" src="https://user-images.githubusercontent.com/23278992/147418147-47f2089f-80ea-4688-ac06-7d9c4b46a08e.png"> <img width="400" src="https://user-images.githubusercontent.com/23278992/147418143-b8f89073-afa1-4c5c-95e9-2ee8a00a94b9.JPG">
Google Drive Link | Size | Output | Original Project | License | year |
---|---|---|---|---|---|
Real ESRGAN4x | 66.9 MB | Image(RGB 2048x2048) | xinntao/Real-ESRGAN | BSD 3-Clause License | 2021 |
Real ESRGAN Anime4x | 66.9 MB | Image(RGB 2048x2048) | xinntao/Real-ESRGAN | BSD 3-Clause License | 2021 |
GFPGAN
Towards Real-World Blind Face Restoration with Generative Facial Prior
<img width="400" src="https://user-images.githubusercontent.com/23278992/186315786-56634605-e357-4e9e-a0d9-51bb526bf69f.png"> <img width="400" src="https://user-images.githubusercontent.com/23278992/186316328-1fc64a6f-a443-4df2-bb86-0af343cd8a64.png">
Google Drive Link | Size | Output | Original Project | License | year |
---|---|---|---|---|---|
GFPGAN | 337.4 MB | Image(RGB 512x512) | TencentARC/GFPGAN | Apache2.0 | 2021 |
BSRGAN
<img width="400" src="https://user-images.githubusercontent.com/23278992/148810656-4c5faa33-1be9-45f6-b31a-defd931cb1f8.jpg"> <img width="400" src="https://user-images.githubusercontent.com/23278992/148811822-56844bc7-b197-44d5-8454-757890c890b5.jpg">
Google Drive Link | Size | Output | Original Project | License | year |
---|---|---|---|---|---|
BSRGAN | 66.9 MB | Image(RGB 2048x2048) | cszn/BSRGAN | 2021 |
A-ESRGAN
<img width="400" src="https://user-images.githubusercontent.com/23278992/151077592-a993a19c-8a05-471a-8924-c7302f7af84b.png"> <img width="400" src="https://user-images.githubusercontent.com/23278992/151077667-62bdbe2b-8e00-4816-945a-14890ccf1bcd.png">
Google Drive Link | Size | Output | Original Project | License | year | Conversion Script |
---|---|---|---|---|---|---|
A-ESRGAN | 63.8 MB | Image(RGB 1024x1024) | aesrgan/A-ESRGANN | BSD 3-Clause License | 2021 |
Beby-GAN
Best-Buddy GANs for Highly Detailed Image Super-Resolution
<img width="400" src="https://user-images.githubusercontent.com/23278992/151282027-14a5d386-60a8-4152-bff1-a0416db81d7a.jpg"> <img width="400" src="https://user-images.githubusercontent.com/23278992/151282014-1177b73d-a2b3-40eb-9a87-9cbe8ace504b.jpg">
Google Drive Link | Size | Output | Original Project | License | year |
---|---|---|---|---|---|
Beby-GAN | 66.9 MB | Image(RGB 2048x2048) | dvlab-research/Simple-SR | MIT | 2021 |
RRDN
The Residual in Residual Dense Network for image super-scaling.
<img width="400" src="https://user-images.githubusercontent.com/23278992/152622988-795c1279-43f7-4d8a-a2ea-a786bcd6a34b.png"> <img width="400" src="https://user-images.githubusercontent.com/23278992/152622984-fbc911c5-901c-4ce3-93b6-753f35dea531.png">
Google Drive Link | Size | Output | Original Project | License | year |
---|---|---|---|---|---|
RRDN | 16.8 MB | Image(RGB 2048x2048) | idealo/image-super-resolution | Apache2.0 | 2018 |
Fast-SRGAN
Fast-SRGAN.
<img width="400" src="https://user-images.githubusercontent.com/23278992/156285673-a6239cec-41ec-46d8-a2fa-d0ad21498f1d.png"> <img width="400" src="https://user-images.githubusercontent.com/23278992/156285686-8d0333a2-b07f-4aa2-8a44-fe959758289f.png">
Google Drive Link | Size | Output | Original Project | License | year |
---|---|---|---|---|---|
Fast-SRGAN | 628 KB | Image(RGB 1024x1024) | HasnainRaz/Fast-SRGAN | MIT | 2019 |
ESRGAN
Enhanced-SRGAN.
<img width="400" src="https://user-images.githubusercontent.com/23278992/156899173-bdc1ceed-c3f6-4abd-b217-18667fc88cf6.jpg"> <img width="400" src="https://user-images.githubusercontent.com/23278992/156899267-65343f4e-a963-4680-83ba-7ecd7e6680a5.jpg">
Google Drive Link | Size | Output | Original Project | License | year |
---|---|---|---|---|---|
ESRGAN | 66.9 MB | Image(RGB 2048x2048) | xinntao/ESRGAN | Apache 2.0 | 2018 |
UltraSharp
Pretrained: 4xESRGAN
<img width="400" src="https://github.com/john-rocky/PersonSegmentationSampler/assets/23278992/b98ab056-23b0-486e-a52c-a88e857c1048"> <img width="400" src="https://github.com/john-rocky/PersonSegmentationSampler/assets/23278992/d4214ded-c9d2-4f18-8de3-222f912862b0">
Google Drive Link | Size | Output | Original Project | License | year |
---|---|---|---|---|---|
UltraSharp | 34 MB | Image(RGB 1024x1024) | Kim2019/ | CC-BY-NC-SA-4.0 | 2021 |
SRGAN
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network.
<img width="400" src="https://user-images.githubusercontent.com/23278992/156899475-172b7ac5-a6ca-4b0b-a6d8-f0d0ddea986e.png"> <img width="400" src="https://user-images.githubusercontent.com/23278992/156899476-641af271-9b2e-4122-a048-099700d8335a.png">
Google Drive Link | Size | Output | Original Project | License | year |
---|---|---|---|---|---|
SRGAN | 6.1 MB | Image(RGB 2048x2048) | dongheehand/SRGAN-PyTorch | 2017 |
SRResNet
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network.
<img width="400" src="https://user-images.githubusercontent.com/23278992/156899905-40746d09-4580-4e30-b0b4-b146fd1975c2.png"> <img width="400" src="https://user-images.githubusercontent.com/23278992/156899906-ab5c8c4e-54af-4d55-874b-5d1e0aac961f.JPG">
Google Drive Link | Size | Output | Original Project | License | year |
---|---|---|---|---|---|
SRResNet | 6.1 MB | Image(RGB 2048x2048) | dongheehand/SRGAN-PyTorch | 2017 |
LESRCNN
Lightweight Image Super-Resolution with Enhanced CNN.
<img width="400" src="https://user-images.githubusercontent.com/23278992/180625941-3a6b44a6-35e1-4ff9-a85b-c5efc81fc101.jpg"> <img width="400" src="https://user-images.githubusercontent.com/23278992/180625939-308f7176-488a-40a1-ab6e-428dc01bbf67.jpg">
Google Drive Link | Size | Output | Original Project | License | year | Conversion Script |
---|---|---|---|---|---|---|
LESRCNN | 4.3 MB | Image(RGB 512x512) | hellloxiaotian/LESRCNN | 2020 |
MMRealSR
Metric Learning based Interactive Modulation for Real-World Super-Resolution
<img width="400" src="https://user-images.githubusercontent.com/23278992/186336018-9c5d5700-28a7-438e-bc07-5ca2a8e843cd.png"> <img width="400" src="https://user-images.githubusercontent.com/23278992/186336038-5e877d1a-33b1-4f54-9e4d-192f9bb765fe.png">
Google Drive Link | Size | Output | Original Project | License | year | Conversion Script |
---|---|---|---|---|---|---|
MMRealSRGAN | 104.6 MB | Image(RGB 1024x1024) | TencentARC/MM-RealSR | BSD 3-Clause | 2022 | |
MMRealSRNet | 104.6 MB | Image(RGB 1024x1024) | TencentARC/MM-RealSR | BSD 3-Clause | 2022 |
DASR
Pytorch implementation of "Unsupervised Degradation Representation Learning for Blind Super-Resolution", CVPR 2021
<img width="400" src="https://github.com/john-rocky/PersonSegmentationSampler/assets/23278992/7e806f4d-0323-431a-89e8-816163e5c3f5"> <img width="400" src="https://github.com/john-rocky/PersonSegmentationSampler/assets/23278992/8589f89b-367d-4777-8ebd-6e78253c4b33">
Google Drive Link | Size | Output | Original Project | License | year |
---|---|---|---|---|---|
DASR | 12.1 MB | Image(RGB 1024x1024) | The-Learning-And-Vision-Atelier-LAVA/DASR | MIT | 2022 |
Low Light Enhancement
StableLLVE
Learning Temporal Consistency for Low Light Video Enhancement from Single Images.
<img width="400" src="https://user-images.githubusercontent.com/23278992/148664179-4d0cd417-d8f9-4d0e-bc05-cff3a4a30b5a.jpg"> <img width="400" src="https://user-images.githubusercontent.com/23278992/148664220-c756198f-e8c5-4ea8-8737-59c004d2f08c.jpg">
Google Drive Link | Size | Output | Original Project | License | Year |
---|---|---|---|---|---|
StableLLVE | 17.3 MB | Image(RGB 512x512) | zkawfanx/StableLLVE | MIT | 2021 |
Zero-DCE
Zero-Reference Deep Curve Estimation for Low-Light Image Enhancement
<img width="400" src="https://user-images.githubusercontent.com/23278992/151897265-7c3c0295-69c3-4c90-9dcc-d04bbcfd41a3.jpg"> <img width="400" src="https://user-images.githubusercontent.com/23278992/151897430-f16d84f0-170c-4e54-a08d-ad4d5b6ca47a.jpg">
Google Drive Link | Size | Output | Original Project | License | Year | Conversion Script |
---|---|---|---|---|---|---|
Zero-DCE | 320KB | Image(RGB 512x512) | Li-Chongyi/Zero-DCE | See Repo | 2021 |
Retinexformer
Retinexformer: One-stage Retinex-based Transformer for Low-light Image Enhancement
<img width="256" src="https://github.com/john-rocky/PersonSegmentationSampler/assets/23278992/296650ba-e2a9-49ba-b2d6-be02e8b56f09"> <img width="256" src="https://github.com/john-rocky/PersonSegmentationSampler/assets/23278992/eac9f78a-2b00-442a-b73f-01760268184e">
Google Drive Link | Size | Output | Original Project | License | Year | Conversion Script |
---|---|---|---|---|---|---|
ZRetinexformer FiveK | 3.4MB | Image(RGB 512x512) | caiyuanhao1998/Retinexformer | MIT | 2023 | |
ZRetinexformer NTIRE | 3.4MB | Image(RGB 512x512) | caiyuanhao1998/Retinexformer | MIT | 2023 |
Image Restoration
MPRNet
Multi-Stage Progressive Image Restoration.
Debluring
<img width="400" src="https://user-images.githubusercontent.com/23278992/149243725-79c68d8e-db6c-4114-ac64-738cd6b5c37c.jpg"> <img width="400" src="https://user-images.githubusercontent.com/23278992/149243509-7eff6ae8-65c2-45ba-bfa2-d730657ab2bd.png">
Denoising
<img width="400" src="https://user-images.githubusercontent.com/23278992/149241165-534c54db-7e98-4356-8613-44acb93d4c6a.png"> <img width="400" src="https://user-images.githubusercontent.com/23278992/149242199-7cc3e456-7c8d-441c-b0aa-f1b6ca19a5c9.png">
Deraining
<img width="400" src="https://user-images.githubusercontent.com/23278992/149241095-91791593-416e-41b0-8a95-71819cb7fb06.jpg"> <img width="400" src="https://user-images.githubusercontent.com/23278992/149241720-afe94607-e9c2-45bb-988d-3c322d7dde1a.jpg">
Google Drive Link | Size | Output | Original Project | License | Year |
---|---|---|---|---|---|
MPRNetDebluring | 137.1 MB | Image(RGB 512x512) | swz30/MPRNet | MIT | 2021 |
MPRNetDeNoising | 108 MB | Image(RGB 512x512) | swz30/MPRNet | MIT | 2021 |
MPRNetDeraining | 24.5 MB | Image(RGB 512x512) | swz30/MPRNet | MIT | 2021 |
MIRNetv2
Learning Enriched Features for Fast Image Restoration and Enhancement.
Denoising
<img width="400" src="https://user-images.githubusercontent.com/23278992/176293658-6715e545-fe9b-4b21-b374-1394740efdde.png"> <img width="400" src="https://user-images.githubusercontent.com/23278992/176293741-dc77831a-86d0-4bdc-a667-96d318d064c4.png">
Super Resolution
<img width="400" src="https://user-images.githubusercontent.com/23278992/176276244-93535414-bc0e-423d-9c0a-18ba432391a4.jpg"> <img width="400" src="https://user-images.githubusercontent.com/23278992/176276266-75228905-2266-4c2c-b42a-026803a0da3b.jpg">
Contrast Enhancement
<img width="400" src="https://user-images.githubusercontent.com/23278992/176286891-563c92cd-1817-406a-babb-7dd9b0cccc01.jpg"> <img width="400" src="https://user-images.githubusercontent.com/23278992/176296935-bce82abf-6420-43ae-924e-5b98ee956431.jpg">
Low Light Enhancement
<img width="400" src="https://user-images.githubusercontent.com/23278992/176283269-145a5ce4-709a-4eea-91a7-b924b598a03d.jpg"> <img width="400" src="https://user-images.githubusercontent.com/23278992/176283354-c45a6247-b1c2-43f8-8b43-8fcf0ddac64f.jpg">
Google Drive Link | Size | Output | Original Project | License | Year | Conversion Script |
---|---|---|---|---|---|---|
MIRNetv2Denoising | 42.5 MB | Image(RGB 512x512) | swz30/MIRNetv2 | ACADEMIC PUBLIC LICENSE | 2022 | |
MIRNetv2SuperResolution | 42.5 MB | Image(RGB 512x512) | swz30/MIRNetv2 | ACADEMIC PUBLIC LICENSE | 2022 | |
MIRNetv2ContrastEnhancement | 42.5 MB | Image(RGB 512x512) | swz30/MIRNetv2 | ACADEMIC PUBLIC LICENSE | 2022 | |
MIRNetv2LowLightEnhancement | 42.5 MB | Image(RGB 512x512) | swz30/MIRNetv2 | ACADEMIC PUBLIC LICENSE | 2022 |
Image Generation
MobileStyleGAN
<img width="400" src="https://user-images.githubusercontent.com/23278992/147397892-773c55ca-55fc-422b-a95b-a729eda04077.JPG"> <img width="400" src="https://user-images.githubusercontent.com/23278992/147397894-e2d3a1ef-7afa-410a-9580-f09ef7157c50.JPG">
Google Drive Link | Size | Output | Original Project | License | Sample Project |
---|---|---|---|---|---|
MobileStyleGAN | 38.6MB | Image(Color 1024 × 1024) | bes-dev/MobileStyleGAN.pytorch | Nvidia Source Code License-NC | CoreML-StyleGAN |
DCGAN
<img width="400" src="https://user-images.githubusercontent.com/23278992/144690829-3a4cebcf-ee73-4df0-b8db-1dfc2e616798.png">Google Drive Link | Size | Output | Original Project |
---|---|---|---|
DCGAN | 9.2MB | MultiArray | TensorFlowCore |
Image2Image
Anime2Sketch
<img width="400" src="https://user-images.githubusercontent.com/23278992/147990751-9ac35e43-b9a6-4db2-af5c-37978322240d.jpeg"> <img width="400" src="https://user-images.githubusercontent.com/23278992/147990892-d676142c-62c4-433d-9835-337b1293bfc4.jpeg">
Google Drive Link | Size | Output | Original Project | License | Usage |
---|---|---|---|---|---|
Anime2Sketch | 217.7MB | Image(Color 512 × 512) | Mukosame/Anime2Sketch | MIT | Drop an image to preview |
AnimeGAN2Face_Paint_512_v2
<img width="400" src="https://camo.qiitausercontent.com/74a02b6e0b80e52c2ae3af798c93eea9aa3e394d/68747470733a2f2f71696974612d696d6167652d73746f72652e73332e61702d6e6f727468656173742d312e616d617a6f6e6177732e636f6d2f302f3233353235392f30313764616563342d333933312d643664662d303339322d6162313039303237313963642e706e67"> <img width="400" src="https://camo.qiitausercontent.com/311349da47136ff9ce61701d09ce59dc663c95bf/68747470733a2f2f71696974612d696d6167652d73746f72652e73332e61702d6e6f727468656173742d312e616d617a6f6e6177732e636f6d2f302f3233353235392f66633337653936332d383533302d333731312d643163662d3335366266646666316665322e706e67">
Google Drive Link | Size | Output | Original Project | Conversion Script |
---|---|---|---|---|
AnimeGAN2Face_Paint_512_v2 | 8.6MB | Image(Color 512 × 512) | bryandlee/animegan2-pytorch |
Photo2Cartoon
<img width="400" src="https://user-images.githubusercontent.com/23278992/147394190-01a2c6be-5056-4f83-b4af-3f494dad47f4.png"> <img width="400" src="https://user-images.githubusercontent.com/23278992/147394192-46de7634-c3ce-481f-afa5-8a7ab4603f2e.png">
Google Drive Link | Size | Output | Original Project | License | Note |
---|---|---|---|---|---|
Photo2Cartoon | 15.2 MB | Image(Color 256 × 256) | minivision-ai/photo2cartoon | MIT | The output is little bit different from the original model. It cause some operations were converted replaced manually. |
AnimeGANv2_Hayao
<img width="400" src="https://user-images.githubusercontent.com/23278992/147421574-8f38367c-d5c5-442d-9742-7b2bb24d43e4.jpg"> <img width="400" src="https://user-images.githubusercontent.com/23278992/147421569-df8e2e59-fef8-4db4-9cb2-65ee960ef705.png">
Google Drive Link | Size | Output | Original Project | Sample |
---|---|---|---|---|
AnimeGANv2_Hayao | 8.7MB | Image(256 x 256) | TachibanaYoshino/AnimeGANv2 | AnimeGANv2-iOS |
AnimeGANv2_Paprika
<img width="400" src="https://user-images.githubusercontent.com/23278992/144670978-1447ce28-db49-4cf9-b484-3142ef703ade.jpg"> <img width="400" src="https://user-images.githubusercontent.com/23278992/144671455-f7258cc9-1a3e-49df-8bbb-03285c619b17.png">
Google Drive Link | Size | Output | Original Project |
---|---|---|---|
AnimeGANv2_Paprika | 8.7MB | Image(256 x 256) | TachibanaYoshino/AnimeGANv2 |
WarpGAN Caricature
<img width="400" src="https://user-images.githubusercontent.com/23278992/147397894-e2d3a1ef-7afa-410a-9580-f09ef7157c50.JPG"> <img width="400" src="https://user-images.githubusercontent.com/23278992/147421276-574edb28-f909-4830-afd0-5cb41328bdba.JPG">
Google Drive Link | Size | Output | Original Project |
---|---|---|---|
WarpGAN Caricature | 35.5MB | Image(256 x 256) | seasonSH/WarpGAN |
UGATIT_selfie2anime
<img width="400" alt="スクリーンショット 2021-12-27 8 18 33" src="https://user-images.githubusercontent.com/23278992/147422391-847b3c75-3e6e-419e-9a53-f6138b9ac813.png"> <img width="400" alt="スクリーンショット 2021-12-27 8 28 11" src="https://user-images.githubusercontent.com/23278992/147422387-2b71a135-cd9c-4f02-8223-65bf365cda4e.png">
Google Drive Link | Size | Output | Original Project |
---|---|---|---|
UGATIT_selfie2anime | 266.2MB(quantized) | Image(256x256) | taki0112/UGATIT |
CartoonGAN
Google Drive Link | Size | Output | Original Project |
---|---|---|---|
CartoonGAN_Shinkai | 44.6MB | MultiArray | mnicnc404/CartoonGan-tensorflow |
CartoonGAN_Hayao | 44.6MB | MultiArray | mnicnc404/CartoonGan-tensorflow |
CartoonGAN_Hosoda | 44.6MB | MultiArray | mnicnc404/CartoonGan-tensorflow |
CartoonGAN_Paprika | 44.6MB | MultiArray | mnicnc404/CartoonGan-tensorflow |
Fast-Neural-Style-Transfer
<img width="400" src="https://user-images.githubusercontent.com/23278992/155708074-ab651a7c-b882-40f1-9ce5-a94e80bac62d.jpg"> <img width="400" src="https://user-images.githubusercontent.com/23278992/155708089-ee888836-3f18-41a1-97fd-72e17e604c9a.jpg"> <img width="400" src="https://user-images.githubusercontent.com/23278992/155707184-403ad161-6354-4ce4-87d4-284e323b1261.jpg"> <img width="400" src="https://user-images.githubusercontent.com/23278992/155708401-f76481ad-1de7-4262-acc2-9dcb61c89784.jpg"> <img width="400" src="https://user-images.githubusercontent.com/23278992/155707199-b77b2583-c355-4406-bc9a-3248492df2c7.jpg"> <img width="400" src="https://user-images.githubusercontent.com/23278992/155706861-97e629a0-4322-4924-94ed-cb10c966bfb8.jpg">
Google Drive Link | Size | Output | Original Project | License | Year |
---|---|---|---|---|---|
fast-neural-style-transfer-cuphead | 6.4MB | Image(RGB 960x640) | eriklindernoren/Fast-Neural-Style-Transfer | MIT | 2019 |
fast-neural-style-transfer-starry-night | 6.4MB | Image(RGB 960x640) | eriklindernoren/Fast-Neural-Style-Transfer | MIT | 2019 |
fast-neural-style-transfer-mosaic | 6.4MB | Image(RGB 960x640) | eriklindernoren/Fast-Neural-Style-Transfer | MIT | 2019 |
White_box_Cartoonization
Learning to Cartoonize Using White-box Cartoon Representations
<img width="400" img src="https://user-images.githubusercontent.com/23278992/189335273-d05f9cdb-1375-4553-8146-2f598676a95b.jpg"> <img width="400" img src="https://user-images.githubusercontent.com/23278992/189335456-5184b222-9b55-429e-850a-adf4879a47fc.jpg">
Google Drive Link | Size | Output | Original Project | License | Year |
---|---|---|---|---|---|
White_box_Cartoonization | 5.9MB | Image(1536x1536) | SystemErrorWang/White-box-Cartoonization | creativecommons | CVPR2020 |
FacialCartoonization
White-box facial image cartoonizaiton
<img width="400" img src="https://user-images.githubusercontent.com/23278992/189454922-1a95ca25-4031-47a7-8914-9fb8e5c7ff58.png"> <img width="400" img src="https://user-images.githubusercontent.com/23278992/189454801-19d6ef20-7361-41a5-b85b-5dbd7cf05adb.png">
Google Drive Link | Size | Output | Original Project | License | Year |
---|---|---|---|---|---|
FacialCartoonization | 8.4MB | Image(256x256) | SystemErrorWang/FacialCartoonization | creativecommons | 2020 |
Inpainting
AOT-GAN-for-Inpainting
<img width="400" src="https://user-images.githubusercontent.com/23278992/220097750-0cd3f94e-1c60-4e03-b9dc-e1ea14f3e57c.gif">Google Drive Link | Size | Output | Original Project | License | Note | Sample Project |
---|---|---|---|---|---|---|
AOT-GAN-for-Inpainting | 60.8MB | MLMultiArray(3,512,512) | researchmm/AOT-GAN-for-Inpainting | Apache2.0 | To use see sample. | john-rocky/Inpainting-CoreML |
Lama
<img width="400" src="https://github.com/john-rocky/PersonSegmentationSampler/assets/23278992/847f874b-7174-4317-8313-f82685bdd20c">Google Drive Link | Size | Input | Output | Original Project | License | Note | Sample Project | Conversion Script |
---|---|---|---|---|---|---|---|---|
Lama | 216.6MB | Image (Color 800 × 800), Image (GrayScale 800 × 800) | Image (Color 800 × 800) | advimman/lama | Apache2.0 | To use see sample. | john-rocky/lama-cleaner-iOS | mallman/CoreMLaMa |
Monocular Depth Estimation
MiDaS
Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer
<img width="400" img src="https://user-images.githubusercontent.com/23278992/224542700-701472b7-fa8c-4824-a966-f9490f7c780f.jpg"> <img width="400" img src="https://user-images.githubusercontent.com/23278992/224542703-11ed535f-40c6-4a45-8e3f-d42ce2b9c6f9.jpeg">
Google Drive Link | Size | Output | Original Project | License | Year | Conversion Script |
---|---|---|---|---|---|---|
MiDaS_Small | 66.3MB | MultiArray(1x256x256) | isl-org/MiDaS | MIT | 2022 |
Stable Diffusion
stable-diffusion-v1-5
<img width="400" alt="スクリーンショット 2023-03-21 18 52 18" src="https://user-images.githubusercontent.com/23278992/226571395-0815ebdb-39e1-4763-bb16-25c33c5ae9bb.png">Google Drive Link | Original Model | Original Project | License | Run on mac | Conversion Script | Year |
---|---|---|---|---|---|---|
stable-diffusion-v1-5 | runwayml/stable-diffusion-v1-5 | runwayml/stable-diffusion | Open RAIL M license | godly-devotion/MochiDiffusion | godly-devotion/MochiDiffusion | 2022 |
pastel-mix
Pastel Mix - a stylized latent diffusion model.This model is intended to produce high-quality, highly detailed anime style with just a few prompts.
<img width="400" alt="スクリーンショット 2023-03-21 19 54 13" src="https://user-images.githubusercontent.com/23278992/226585761-3eaba244-7fea-4529-af36-0962fe624936.png">Google Drive Link | Original Model | License | Run on mac | Conversion Script | Year |
---|---|---|---|---|---|
pastelMixStylizedAnime_pastelMixPrunedFP16 | andite/pastel-mix | Fantasy.ai | godly-devotion/MochiDiffusion | godly-devotion/MochiDiffusion | 2023 |
Orange Mix
<img width="800" alt="スクリーンショット 2023-03-21 23 34 13" src="https://user-images.githubusercontent.com/23278992/226656177-8260d83c-6e93-4d9b-8fbd-154a0028f88d.png">Google Drive Link | Original Model | License | Run on mac | Conversion Script | Year |
---|---|---|---|---|---|
AOM3_orangemixs | WarriorMama777/OrangeMixs | CreativeML OpenRAIL-M | godly-devotion/MochiDiffusion | godly-devotion/MochiDiffusion | 2023 |
Counterfeit
<img width="800" alt="スクリーンショット 2023-03-22 0 47 53" src="https://user-images.githubusercontent.com/23278992/226731352-c6ad077d-6f91-4a03-a6e5-dd01ce398d9c.png">Google Drive Link | Original Model | License | Run on mac | Conversion Script | Year |
---|---|---|---|---|---|
Counterfeit-V2.5 | gsdf/Counterfeit-V2.5 | - | godly-devotion/MochiDiffusion | godly-devotion/MochiDiffusion | 2023 |
anything-v4
<img width="800" alt="スクリーンショット 2023-03-22 0 47 53" src="https://user-images.githubusercontent.com/23278992/226734890-8b48320f-5b4c-4f6c-bd56-07954f573582.png">Google Drive Link | Original Model | License | Run on mac | Conversion Script | Year |
---|---|---|---|---|---|
anything-v4.5 | andite/anything-v4.0 | Fantasy.ai | godly-devotion/MochiDiffusion | godly-devotion/MochiDiffusion | 2023 |
Openjourney
<img width="800" alt="スクリーンショット 2023-03-22 7 49 39" src="https://user-images.githubusercontent.com/23278992/226909583-42efdb55-e2f0-4331-be0d-7f4bcd2c8b2c.png">Google Drive Link | Original Model | License | Run on mac | Conversion Script | Year |
---|---|---|---|---|---|
Openjourney | prompthero/openjourney | - | godly-devotion/MochiDiffusion | godly-devotion/MochiDiffusion | 2023 |
dreamlike-photoreal-2
<img width="800" alt="dreamlike" src="https://user-images.githubusercontent.com/23278992/226922948-1af2334b-0798-4aef-bfb4-464438dde1b9.png">Google Drive Link | Original Model | License | Run on mac | Conversion Script | Year |
---|---|---|---|---|---|
dreamlike-photoreal-2.0 | dreamlike-art/dreamlike-photoreal-2.0 | CreativeML OpenRAIL-M | godly-devotion/MochiDiffusion | godly-devotion/MochiDiffusion | 2023 |
Models converted by someone other than me.
Stable Diffusion
How to use in a xcode project.
Option 1,implement Vision request.
import Vision
lazy var coreMLRequest:VNCoreMLRequest = {
let model = try! VNCoreMLModel(for: modelname().model)
let request = VNCoreMLRequest(model: model, completionHandler: self.coreMLCompletionHandler)
return request
}()
let handler = VNImageRequestHandler(ciImage: ciimage,options: [:])
DispatchQueue.global(qos: .userInitiated).async {
try? handler.perform([coreMLRequest])
}
If the model has Image type output:
let result = request?.results?.first as! VNPixelBufferObservation
let uiimage = UIImage(ciImage: CIImage(cvPixelBuffer: result.pixelBuffer))
Else the model has Multiarray type output:
For visualizing multiArray as image, Mr. Hollance’s “CoreML Helpers” are very convenient. CoreML Helpers
Converting from MultiArray to Image with CoreML Helpers.
func coreMLCompletionHandler(request:VNRequest?、error:Error?){
let = coreMLRequest.results?.first as!VNCoreMLFeatureValueObservation
let multiArray = result.featureValue.multiArrayValue
let cgimage = multiArray?.cgImage(min:-1、max:1、channel:nil)
Option 2,Use CoreGANContainer. You can use models with dragging&dropping into the container project.
Make the model lighter
You can make the model size lighter with Quantization if you want. https://coremltools.readme.io/docs/quantization
The lower the number of bits, more the chances of degrading the model accuracy. The loss in accuracy varies with the model.
import coremltools as ct
from coremltools.models.neural_network import quantization_utils
# load full precision model
model_fp32 = ct.models.MLModel('model.mlmodel')
model_fp16 = quantization_utils.quantize_weights(model_fp32, nbits=16)
# nbits can be 16(half size model), 8(1/4), 4(1/8), 2, 1
quantized sample (U2Net)
InputImage / nbits=32(original) / nbits=16 / nbits=8 / nbits=4
<img src="https://user-images.githubusercontent.com/23278992/147712147-0959c0b9-9d4b-4049-9dd9-7a9d1ffa0eed.JPEG" width=200> <img src="https://user-images.githubusercontent.com/23278992/147712215-dd0c8788-75ad-4676-804a-fdd47233daa6.JPG" width=200> <img src="https://user-images.githubusercontent.com/23278992/147712220-d02ab436-9716-4cdc-91d3-8b6f3aa01fac.JPG" width=200> <img src="https://user-images.githubusercontent.com/23278992/147712259-aabf5ecf-db59-476d-8f36-e6027dfb91e2.JPG" width=200> <img src="https://user-images.githubusercontent.com/23278992/147712328-a44f538c-aa3e-431d-98ec-626239262e01.JPG" width=200>
Thanks
Cover image was taken from Ghibli free images.
On YOLOv5 convertion, dbsystel/yolov5-coreml-tools give me the super inteligent convert script.
And all of original projects
Auther
Daisuke Majima Freelance engineer. iOS/MachineLearning/AR I can work on mobile ML projects and AR project. Feel free to contact: rockyshikoku@gmail.com