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Ikomia HUB

State-of-the-art Computer Vision as ready-to-use algorithms

State-of-the-art Computer Vision as ready-to-use algorithms

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Introduction

At Ikomia, we deeply believe that sharing scientific knowledge is the key to success, that's why we make research-based algorithms ready-to-use for developers.

The main goal of Ikomia is to take existing Python code and wrap it as ready-to-use algorithm for Ikomia API (our Python library) and Ikomia STUDIO (our desktop software). With this approach, we can easily integrate individual repos from researchers or labs and also awesome frameworks like OpenCV, Detectron2, OpenMMLab or Hugging Face so that developers can benefit from the best state-of-the-art algorithms in a single framework.

Table of Contents
  1. Dataset loader
  2. Classification
  3. Colorization
  4. Image captioning
  5. Image generation
  6. Image matting
  7. Inpainting
  8. Instance segmentation
  9. Keypoints detection
  10. Object Detection
  11. Object tracking
  12. OCR
  13. Optical flow
  14. Other
  15. Panoptic segmentation
  16. Semantic segmentation
  17. Super resolution

Dataset loader

Name Language Description Original repository
auto_annotate Python Auto-annotate images with GroundingDINO and SAM models Made by Ikomia
dataset_classification Python Load classification dataset Made by Ikomia
dataset_coco Python Load COCO 2017 dataset Made by Ikomia
dataset_cwfid Python Load Crop/Weed Field Image Dataset (CWFID) for semantic segmentation Link
dataset_pascal_voc Python Load PascalVOC dataset Made by Ikomia
dataset_via Python Load VGG Image Annotator dataset Made by Ikomia
dataset_wgisd Python Load Wine Grape Instance Segmentation Dataset (WGISD) Link
dataset_wildreceipt Python Load Wildreceipt dataset Made by Ikomia
dataset_yolo Python Load YOLO dataset Made by Ikomia

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Classification

Name Language Description Original repository
infer_covidnet Python A tailored Deep Convolutional Neural Network Design for detection of COVID-19 cases from chest radiography images. Link
infer_emotion_fer_plus Python Facial emotion recognition using DNN trained from crowd-sourced label distribution. Link
infer_resnet_action_recognition Python Human action recognition with spatio-temporal 3D CNNs. Link
infer_timm_image_classification Python Infer timm image classification models Link
infer_torchvision_mnasnet Python MnasNet inference model for image classification. Link
infer_torchvision_resnet Python ResNet inference model for image classification. Link
infer_torchvision_resnext Python ResNeXt inference model for image classification. Link
infer_yolo_v8_classification Python Inference with YOLOv8 image classification models Made by Ikomia
train_timm_image_classification Python Train timm image classification models Link
train_torchvision_mnasnet Python Training process for MnasNet convolutional network. Link
train_torchvision_resnet Python Training process for ResNet convolutional network. Link
train_torchvision_resnext Python Training process for ResNeXt convolutional network. Link
train_yolo_v8_classification Python Train YOLOv8 classification models. Made by Ikomia

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Colorization

Name Language Description Original repository
infer_colorful_image_colorization Python Automatic colorization of grayscale image based on neural network. Link

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Image generation

Name Language Description Original repository
infer_hf_stable_diffusion Python Stable diffusion models from Hugging Face. Link
infer_kandinsky_2 Python Kandinsky 2.2 text2image diffusion model. Link
infer_kandinsky_2_controlnet_depth Python Kandinsky 2.2 controlnet depth diffusion model. Link
infer_kandinsky_2_image_mixing Python Kandinsky 2.2 image mixing diffusion model. Link
infer_kandinsky_2_img2img Python Kandinsky 2.2 image-to-image diffusion model. Link
infer_neural_style_transfer Python Neural network method to paint given image in the style of the reference image. Link
infer_pulid Python Pure and Lightning ID customization (PuLID) is a novel tuning-free ID customization method for text-to-image generation. Link
infer_stable_cascade Python Stable Cascade is a diffusion model trained to generate images given a text prompt. Link

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Image matting

Name Language Description Original repository
infer_background_matting Python Real-Time High-Resolution Background Matting Link
infer_modnet_portrait_matting Python Inference of MODNet Portrait Matting. Link
infer_p3m_portrait_matting Python Inference of Privacy-Preserving Portrait Matting (P3M) Link

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Inpainting

Name Language Description Original repository
infer_face_inpainting Python Face inpainting using Segformer for segmentation and RealVisXL for inpainting. Made by Ikomia
infer_hf_stable_diffusion_inpaint Python Stable diffusion inpainting models from Hugging Face. Link
infer_kandinsky_2_inpaint Python Kandinsky 2.2 inpainting diffusion model. Link

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Instance segmentation

Name Language Description Original repository
infer_detectron2_instance_segmentation Python Infer Detectron2 instance segmentation models Link
infer_detectron2_pointrend Python PointRend inference model of Detectron2 for instance segmentation. Link
infer_hf_instance_seg Python Instance segmentation using models from Hugging Face. Link
infer_sparseinst Python Infer Sparseinst instance segmentation models Link
infer_torchvision_mask_rcnn Python Mask R-CNN inference model for object detection and segmentation. Link
infer_yolact Python A simple, fully convolutional model for real-time instance segmentation. Link
infer_yolo_v7_instance_segmentation Python Inference for YOLO v7 instance segmentation models Link
infer_yolo_v8_seg Python Inference with YOLOv8 segmentation models Link
infer_yolop_v2 Python Panoptic driving Perception using YoloPv2 Link
train_detectron2_instance_segmentation Python Train Detectron2 instance segmentation models Link
train_mmlab_segmentation Python Train for MMLAB segmentation models Link
train_sparseinst Python Train Sparseinst instance segmentation models Link
train_torchvision_mask_rcnn Python Training process for Mask R-CNN convolutional network. Link
train_yolo_v7_instance_segmentation Python Train for YOLO v7 instance segmentation models Link
train_yolo_v8_seg Python Train YOLOv8 instance segmentation models. Link

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Keypoints detection

Name Language Description Original repository
infer_detectron2_densepose Python Detectron2 inference model for human pose detection. Link
infer_detectron2_keypoints Python Inference for Detectron2 keypoint models Link
infer_mmlab_pose_estimation Python Inference for pose estimation models from mmpose Link
infer_yolo_v7_keypoints Python YOLOv7 pose estimation models. Link
infer_yolo_v8_pose_estimation Python Inference with YOLOv8 pose estimation models Link

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Object Detection

Name Language Description Original repository
infer_detectron2_detection Python Inference for Detectron2 detection models Link
infer_detectron2_retinanet Python RetinaNet inference model of Detectron2 for object detection. Link
infer_detectron2_tridentnet Python TridentNet inference model of Detectron2 for object detection. Link
infer_face_detection_kornia Python Face detection using the Kornia API Link
infer_google_vision_face_detection Python Face detection using Google cloud vision API. Link
infer_google_vision_landmark_detection Python Landmark Detection detects popular natural and human-made structures within an image. Link
infer_google_vision_logo_detection Python Logo Detection detects popular product logos within an image using the Google cloud vision API. Link
infer_google_vision_object_localization Python The Vision API can detect and extract multiple objects in an image with Object Localization. Link
infer_grounding_dino Python Inference of the Grounding DINO model Link
infer_mmlab_detection Python Inference for MMDET from MMLAB detection models Link
infer_torchvision_faster_rcnn Python Faster R-CNN inference model for object detection. Link
infer_yolo_v5 Python Ultralytics YoloV5 object detection models. Made by Ikomia
infer_yolo_v7 Python YOLOv7 object detection models. Link
infer_yolo_v8 Python Inference with YOLOv8 models Link
infer_yolo_v9 Python Object detection with YOLOv9 models Link
infer_yolo_v10 Python Run inference with YOLOv10 models Link
infer_yolo_world Python YOLO-World is a real-time zero-shot object detection modelthat leverages the power of open-vocabulary learning to recognize and localize a wide range of objects in images. Link
infer_yolop_v2 Python Panoptic driving Perception using YoloPv2 Link
infer_yolor Python Inference for YoloR object detection models Link
train_detectron2_detection Python Train for Detectron2 detection models Link
train_mmlab_detection Python Train for MMLAB detection models Link
train_torchvision_faster_rcnn Python Training process for Faster R-CNN convolutional network. Link
train_yolo_v5 Python Train Ultralytics YoloV5 object detection models. Link
train_yolo_v7 Python Train YOLOv7 object detection models. Link
train_yolo_v8 Python Train YOLOv8 object detection models. Link
train_yolo_v9 Python Train YOLOv9 models Link
train_yolo_v10 Python Train YOLOv10 object detection models. Link
train_yolor Python Train YoloR object detection models Link

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Object tracking

Name Language Description Original repository
infer_bytetrack Python Infer ByteTrack for object tracking Link
infer_deepsort Python Multiple Object Tracking algorithm (MOT) combining a deep association metricwith the well known SORT algorithm for better performance. Link

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OCR

Name Language Description Original repository
infer_google_vision_ocr Python Detects and extracts text from any image. Link
infer_mmlab_text_detection Python Inference for MMOCR from MMLAB text detection models Link
infer_mmlab_text_recognition Python Inference for MMOCR from MMLAB text recognition models Link
train_mmlab_kie Python Train for MMOCR from MMLAB KIE models Link
train_mmlab_text_detection Python Training process for MMOCR from MMLAB in text detection Link
train_mmlab_text_recognition Python Training process for MMOCR from MMLAB in text recognition Link

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Optical flow

Name Language Description Original repository
infer_raft_optical_flow Python Estimate the optical flow from a video using a RAFT model. Link

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Other

Name Language Description Original repository
infer_depth_anything Python Depth Anything is a highly practical solution for robust monocular depth estimation Link
infer_google_vision_image_properties Python Image Properties feature detects general attributes of the image, such as dominant color. Link
infer_google_vision_label_detection Python Detect and extract information about entities in an image, across a broad group of categories. Link
infer_google_vision_safe_search Python Safe Search detects explicit content such as adult content or violent content within an image. Link
infer_google_vision_web_detection Python Web Detection detects Web references to an image. Link

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Panoptic segmentation

Name Language Description Original repository
infer_detectron2_panoptic_segmentation Python Infer Detectron2 panoptic segmentation models Made by Ikomia
infer_hf_image_seg Python Panoptic segmentation using models from Hugging Face. Made by Ikomia
infer_mmlab_segmentation Python Inference for MMLAB segmentation models Link
train_mmlab_segmentation Python Train for MMLAB segmentation models Link

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Semantic segmentation

Name Language Description Original repository
infer_detectron2_deeplabv3plus Python DeepLabv3+ inference model of Detectron2 for semantic segmentation. Link
infer_hf_semantic_seg Python Semantic segmentation using models from Hugging Face. Link
infer_mmlab_segmentation Python Inference for MMLAB segmentation models Link
infer_mobile_segment_anything Python Inference for Mobile Segment Anything Model (SAM). Link
infer_segment_anything Python Inference for Segment Anything Model (SAM). Link
infer_transunet Python TransUNet inference for semantic segmentation Link
infer_unet Python Multi-class semantic segmentation using Unet, the default model was trained on Kaggle's Carvana Images dataset Link
infer_yolop_v2 Python Panoptic driving Perception using YoloPv2 Link
train_detectron2_deeplabv3plus Python Training process for DeepLabv3+ model of Detectron2. Link
train_hf_semantic_seg Python Train models for semantic segmentationwith transformers from HuggingFace. Link
train_mmlab_segmentation Python Train for MMLAB segmentation models Link
train_transunet Python Training process for TransUNet model. Link
train_unet Python multi-class semantic segmentation using Unet Link

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Super resolution

Name Language Description Original repository
infer_swinir_super_resolution Python Image restoration algorithms with Swin Transformer Made by Ikomia

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