Randl / Mobilenetv2 Pytorch
Licence: mit
Impementation of MobileNetV2 in pytorch
Stars: ✭ 241
Programming Languages
python
139335 projects - #7 most used programming language
Projects that are alternatives of or similar to Mobilenetv2 Pytorch
Deepmodels
TensorFlow Implementation of state-of-the-art models since 2012
Stars: ✭ 33 (-86.31%)
Mutual labels: cnn, image-classification
Fast Autoaugment
Official Implementation of 'Fast AutoAugment' in PyTorch.
Stars: ✭ 1,297 (+438.17%)
Mutual labels: cnn, image-classification
Meme Generator
MemeGen is a web application where the user gives an image as input and our tool generates a meme at one click for the user.
Stars: ✭ 57 (-76.35%)
Mutual labels: cnn, image-classification
Rmdl
RMDL: Random Multimodel Deep Learning for Classification
Stars: ✭ 375 (+55.6%)
Mutual labels: cnn, image-classification
Autoclint
A specially designed light version of Fast AutoAugment
Stars: ✭ 171 (-29.05%)
Mutual labels: cnn, image-classification
Pytorch classification
利用pytorch实现图像分类的一个完整的代码，训练，预测，TTA，模型融合，模型部署，cnn提取特征，svm或者随机森林等进行分类，模型蒸馏，一个完整的代码
Stars: ✭ 395 (+63.9%)
Mutual labels: cnn, image-classification
Wb color augmenter
WB color augmenter improves the accuracy of image classification and image semantic segmentation methods by emulating different WB effects (ICCV 2019) [Python & Matlab].
Stars: ✭ 89 (-63.07%)
Mutual labels: cnn, image-classification
Facial Expression Recognition Using Cnn
Deep facial expressions recognition using Opencv and Tensorflow. Recognizing facial expressions from images or camera stream
Stars: ✭ 261 (+8.3%)
Mutual labels: cnn, image-classification
Iresnet
Improved Residual Networks (https://arxiv.org/pdf/2004.04989.pdf)
Stars: ✭ 163 (-32.37%)
Mutual labels: cnn, image-classification
Image classifier
CNN image classifier implemented in Keras Notebook 🖼️.
Stars: ✭ 139 (-42.32%)
Mutual labels: cnn, image-classification
Mobilenetv2
A Keras implementation of MobileNetV2.
Stars: ✭ 277 (+14.94%)
Mutual labels: cnn, image-classification
Deep Learning With Python
Deep learning codes and projects using Python
Stars: ✭ 195 (-19.09%)
Mutual labels: cnn, image-classification
Pytorch Image Classification
Tutorials on how to implement a few key architectures for image classification using PyTorch and TorchVision.
Stars: ✭ 272 (+12.86%)
Mutual labels: cnn, image-classification
Quickdraw
Implementation of Quickdraw - an online game developed by Google
Stars: ✭ 805 (+234.02%)
Mutual labels: cnn, image-classification
Resnetcam Keras
Keras implementation of a ResNet-CAM model
Stars: ✭ 269 (+11.62%)
Mutual labels: cnn, image-classification
Tf Mobilenet V2
Mobilenet V2(Inverted Residual) Implementation & Trained Weights Using Tensorflow
Stars: ✭ 85 (-64.73%)
Mutual labels: cnn, image-classification
Keras transfer cifar10
Object classification with CIFAR-10 using transfer learning
Stars: ✭ 120 (-50.21%)
Mutual labels: cnn, image-classification
Beauty Net
A simple, flexible, and extensible template for PyTorch. It's beautiful.
Stars: ✭ 190 (-21.16%)
Mutual labels: cnn, image-classification
Transfer Learning Suite
Transfer Learning Suite in Keras. Perform transfer learning using any built-in Keras image classification model easily!
Stars: ✭ 212 (-12.03%)
Mutual labels: cnn, image-classification
Srgan
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
Stars: ✭ 2,641 (+995.85%)
Mutual labels: cnn
MobileNetv2 in PyTorch
An implementation of MobileNetv2 in PyTorch. MobileNetv2 is an efficient convolutional neural network architecture for mobile devices. For more information check the paper:
Inverted Residuals and Linear Bottlenecks: Mobile Networks for Classification, Detection and Segmentation
Usage
Clone the repo:
git clone https://github.com/Randl/MobileNetV2-pytorch
pip install -r requirements.txt
Use the model defined in model.py to run ImageNet example:
python imagenet.py --dataroot "/path/to/imagenet/"
To run continue training from checkpoint
python imagenet.py --dataroot "/path/to/imagenet/" --resume "/path/to/checkpoint/folder"
Results
For x1.0 model I achieved 0.3% higher top-1 accuracy than claimed.
| Classification Checkpoint | MACs (M) | Parameters (M) | Top-1 Accuracy | Top-5 Accuracy | Claimed top-1 | Claimed top-5 |
|---|---|---|---|---|---|---|
| [mobilenet_v2_1.0_224] | 300 | 3.47 | 72.10 | 90.48 | 71.8 | 91.0 |
| [mobilenet_v2_0.5_160] | 50 | 1.95 | 60.61 | 82.87 | 61.0 | 83.2 |
You can test it with
python imagenet.py --dataroot "/path/to/imagenet/" --resume "results/mobilenet_v2_1.0_224/model_best.pth.tar" -e
python imagenet.py --dataroot "/path/to/imagenet/" --resume "results/mobilenet_v2_0.5_160/model_best.pth.tar" -e --scaling 0.5 --input-size 160
Note that the project description data, including the texts, logos, images, and/or trademarks,
for each open source project belongs to its rightful owner.
If you wish to add or remove any projects, please contact us at [email protected].