NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite
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Updated
Jul 4, 2024 - Python
NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite
Bio Sortify is an image classification ML model trained to classify waste as either biodegradable or non-biodegradable.
Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale.
Predicting geolocations from pictures, research project done at HSLU. Open dataset:
Image Recognition Implementation from scratch using TensorFlowJS
Parametric Contrastive Learning (ICCV2021) & GPaCo (TPAMI 2023)
A text and media analysis service for Meedan Check, a collaborative media annotation platform
Computer Vision Techniques Unlock the potential of computer vision with my repository. From fundamental algorithms to advanced techniques, explore implementations using OpenCV, TensorFlow, and PyTorch for seamless integration and learning.
Image classification of superficial fungal infections (dermatomycoses) with CNNs and Transfer Learning (EfficientNetV2)
This repository holds all the project files belongs to a Kidney diesease classification application which takes x-rays images and classify the image as dieseased or healthy by using Deep learning CNN classification techniques.
Cheque Detection using Yolov8. A model to verify and detect various parts bank cheques.
Image Content Filtering Using CNN and Transfer Learning
ECCV 2024 论文和开源项目合集,同时欢迎各位大佬提交issue,分享ECCV 2024论文和开源项目
Experience the power of Clarifai’s AI platform with the python SDK. 🌟 Star to support our work!
[CVPR 2024 Oral] InternVL Family: A Pioneering Open-Source Alternative to GPT-4V. 接近GPT-4V表现的可商用开源多模态对话模型
Label Studio is a multi-type data labeling and annotation tool with standardized output format
This repository is dedicated to small projects and some theoretical material that I used to get into Computer Vision using TensorFlow in a practical and efficient way.
From Python basics to Machine Learning and PyTorch Deep Learning - one day at a time, explore it all
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