deeplab2 VS yolov7

Compare deeplab2 vs yolov7 and see what are their differences.

deeplab2

DeepLab2 is a TensorFlow library for deep labeling, aiming to provide a unified and state-of-the-art TensorFlow codebase for dense pixel labeling tasks. (by google-research)

yolov7

Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors (by WongKinYiu)
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deeplab2 yolov7
5 33
980 12,530
0.9% -
4.0 4.0
12 months ago about 1 month ago
Python Jupyter Notebook
Apache License 2.0 GNU General Public License v3.0 only
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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deeplab2

Posts with mentions or reviews of deeplab2. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-08-06.

yolov7

Posts with mentions or reviews of yolov7. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-10-17.

What are some alternatives?

When comparing deeplab2 and yolov7 you can also consider the following projects:

yolov3 - YOLOv3 in PyTorch > ONNX > CoreML > TFLite

edgetpu - Coral issue tracker (and legacy Edge TPU API source)

edgetpu-yolo - Minimal-dependency Yolov5 export and inference demonstration for the Google Coral EdgeTPU

YOLOv4 - Port of YOLOv4 to C# + TensorFlow

darknet - Convolutional Neural Networks

XMem - [ECCV 2022] XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model

BCNet - Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers [CVPR 2021]

CATNet - 🛰️ Learning to Aggregate Multi-Scale Context for Instance Segmentation in Remote Sensing Images (TNNLS 2023)

yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

yolact - A simple, fully convolutional model for real-time instance segmentation.

YOLOv6 - YOLOv6: a single-stage object detection framework dedicated to industrial applications.

Cream - This is a collection of our NAS and Vision Transformer work. [Moved to: https://github.com/microsoft/AutoML]