- efficientdet-pytorch VS Pytorch-UNet
- efficientdet-pytorch VS Yet-Another-EfficientDet-Pytorch
- efficientdet-pytorch VS segmentation_models.pytorch
- efficientdet-pytorch VS darknet
- efficientdet-pytorch VS InternImage
- efficientdet-pytorch VS automl
- efficientdet-pytorch VS involution
- efficientdet-pytorch VS flying-guide-dog
- efficientdet-pytorch VS ros-semantic-segmentation-pytorch
- efficientdet-pytorch VS mmsegmentation
Efficientdet-pytorch Alternatives
Similar projects and alternatives to efficientdet-pytorch
-
darknet
YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet ) (by AlexeyAB)
-
Stream
Stream - Scalable APIs for Chat, Feeds, Moderation, & Video. Stream helps developers build engaging apps that scale to millions with performant and flexible Chat, Feeds, Moderation, and Video APIs and SDKs powered by a global edge network and enterprise-grade infrastructure.
-
Yet-Another-EfficientDet-Pytorch
The pytorch re-implement of the official efficientdet with SOTA performance in real time and pretrained weights.
-
Pytorch-UNet
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
-
segmentation_models.pytorch
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
-
InternImage
[CVPR 2023 Highlight] InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions
-
-
involution
[CVPR 2021] Involution: Inverting the Inherence of Convolution for Visual Recognition, a brand new neural operator
-
InfluxDB
InfluxDB – Built for High-Performance Time Series Workloads. InfluxDB 3 OSS is now GA. Transform, enrich, and act on time series data directly in the database. Automate critical tasks and eliminate the need to move data externally. Download now.
-
flying-guide-dog
Official implementation of "Flying Guide Dog: Walkable Path Discovery for the Visually Impaired Utilizing Drones and Transformer-based Semantic Segmentation", IEEE ROBIO 2021
-
ros-semantic-segmentation-pytorch
Pytorch implementation of Semantic Segmentation in ROS on MIT ADE20K dataset based on semantic-segmentation-pytorch by CSAIL
-
efficientdet-pytorch discussion
efficientdet-pytorch reviews and mentions
- Bounding box annotations and object orientation
However, there are papers on oriented object detectors (see https://arxiv.org/pdf/1911.07732.pdf) for example. In that paper, they do achieve better results using oriented bounding boxes. If you want to go down that route, I would suggest using the EfficientDet model, because the PyTorch code that you'll find for it is quite easy to understand and modify. For example, I've taken https://github.com/zylo117/Yet-Another-EfficientDet-Pytorch, and modified it to include a "thing-ness" logit, and this was pretty easy to do. Classic EfficientDet models only include logits (aka output neurons that get softmax-ed) for each class, and if any one of these class neurons is greater than 0.5, then it is considered "a thing". Anyway - that's digression, but my point is that I've thought about adding oriented box support to an EfficientDet model, and it didn't seem to be too hard, although I haven't actually done it. If I was to start now, I would probably go with https://github.com/rwightman/efficientdet-pytorch, since Ross Wightman's models are becoming a de-facto standard in the PyTorch world for all things image-related.
Stats
rwightman/efficientdet-pytorch is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of efficientdet-pytorch is Python.