Reverse Dependencies of coremltools

The following projects have a declared dependency on coremltools:

• asone — no summary
• basic-pitch — Basic Pitch, a lightweight yet powerful audio-to-MIDI converter with pitch bend detection.
• bianbu-ai-toolkit-caffe — Bianbu AI Toolkit
• coreml-pytorch-utils — Coreml utils that helps export pytorch based models
• doclayout-yolo — DocLayout-YOLO: an effecient and robust document layout analysis method.
• fastnn — A python library and framework for fast neural network computations.
• imagedetect — Ultralytics YOLOv8
• improveai — Improve AI: AI Decisions for iOS, Android, and the Cloud
• kraken — OCR/HTR engine for all the languages
• kraken-didip — OCR/HTR engine for all the languages: a fork for the DiDip project.
• mera-tvm-runtime — Mera TVM: An End to End Tensor IR/DSL Stack for Deep Learning Systems, adapted to Mera (https://github.com/Edgecortix-Inc/mera) environment.
• modelutils — Utility scripts for various deep learning models
• mxnet-coreml-converter — Tool to convert MXNet models into Apple CoreML model format.
• mxnet-to-coreml — Tool to convert MXNet models into Apple CoreML model format.
• ng-fruitdetect — A short description of your package
• onnx-coreml — Convert ONNX (Open Neural Network Exchange)models into Apple CoreML format.
• openpifpaf — PifPaf: Composite Fields for Human Pose Estimation
• osmosis — An experimental Stable Diffusion frontend
• pyppbox-ultralytics — Ultralytics YOLOv8 for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification.
• pysipfenn — Python toolset for Structure-Informed Property and Feature Engineering with Neural Networks. It offers unique advantages through (1) effortless extensibility, (2) optimizations for ordered, dilute, and random atomic configurations, and (3) automated model tuning.
• qai-hub — Python API for Qualcomm® AI Hub.
• quickAI — QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
• rheioyu58 — no summary
• roar-yolo — Ultralytics YOLOv8
• stablehlo-coreml-experimental — Convert StableHLO models into Apple Core ML format
• syml-ultralytics — Ultralytics YOLO 🚀 for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification.
• tetra-hub — Python API for Tetra Hub.
• Tetra-Model-Zoo — Models optimized for export to run on device.
• tfcoreml — TensorFlow to Core ML converter
• UltraDetect — Customized Ultralytics YOLO for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification.
• ultralytics — Ultralytics YOLO 🚀 for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification.
• ultralytics-dev — Ultralytics YOLOv8 for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification.
• ultralytics-dist-yolo — Ultralytics YOLOv8 for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification.
• ultralytics-export-to-rknn — Ultralytics YOLOv8 for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification.
• ultralytics-nogui — Ultralytics YOLOv8 for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification.
• ultralytics-rknn — Ultralytics YOLOv8 for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification.
• ultralytics-v11 — Ultralytics YOLO for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification.
• ultralytics-yolov10-rknn — Ultralytics YOLOv8 for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification.
• ultralyticsheadless — Ultralytics YOLO 🚀 for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification.
• vsensebox-ultralytics — Ultralytics YOLO for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification.
• whisper-ane — ANE optimised adaptation of Whisper for optimised inference
• xn-ultralytics — This is a public fork of Ultralytics YOLOv8 for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification. Free for anyone to use, for non-commercial purposes.
• ymsyolo10 — Ultralytics YOLOv8 for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification.
• yolotest — Ultralytics YOLOv8
• yolov8-pose-triton — Ultralytics YOLOv8 for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification.
• yolov8-rknn — Ultralytics YOLOv8 for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification.
• zipvehicle — no summary