netron
PINTO_model_zoo
| netron | PINTO_model_zoo | |
|---|---|---|
| 33 | 5 | |
| 26,110 | 3,301 | |
| - | - | |
| 9.9 | 9.7 | |
| 5 days ago | 3 days ago | |
| JavaScript | Python | |
| MIT License | MIT License |
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netron
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What's the best PyTorch model visualization tool?
Netron seems to be the best that I've seen so far. https://github.com/lutzroeder/netron
- Visualizer for neural network, deep learning and machine learning models
- Netron: Visualizer for Machine Learning Models
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Exploring Open-Source Alternatives to Landing AI for Robust MLOps
In exploring open-source projects, I've come across several promising tools capable of managing deep-learning models for images. Significantly, tools such as NETRON provide visualization of neural networks, while SHAP can be used for evaluating the significance of outputs.
- Netron is a viewer for neural network, deep learning and machine learning models
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Operationalize TensorFlow Models With ML.NET
We need to find out the exact input and output tensor names. A tool like Netron makes this super easy. Open the original .tflite and/or the ONNX model in Netron and click the Model Properties button in the lower left corner.
- Netron: A viewer for neural network, deep learning and machine learning models
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Visualize PyTorch Models with NNViz
How is this different from e.g Netron https://github.com/lutzroeder/netron
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[P]Visualizing a neural network.
Netron (https://netron.app/) is the best and mostly used NN visualizer. Just save your model and then simply load it via netron to look its layers and weights. If you want a more complex visualization then you can also play with Zetane ( but its paid, also have a free version) engine.
- How do I visualize this NN Architecture?
PINTO_model_zoo
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YOLOv7 object detection in Ruby in 10 minutes
Download the ONNX model from this project: 307_YOLOv7
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stereodemo: compare several recent stereo depth estimation methods in the wild
Hope it might be useful to more people, and thanks to PINTO0309 and ibaiGorordo for converting several pre-trained models to ONNX!
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Loading Saved Models for transfer learning
Check it out https://github.com/PINTO0309/PINTO_model_zoo
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[R][P]MobileStyleGAN: A Lightweight Convolutional Neural Network for High-Fidelity Image Synthesis
Someone reported, that he converted MobileStyleGAN to tfjs (https://github.com/PINTO0309/PINTO_model_zoo), but i didn't check it
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Can we increase the output class in transfer learning?
model:-https://github.com/PINTO0309/PINTO_model_zoo/blob/main/053_BlazePose/01_float32/02_pose_landmark_upper_body_tflite2h5_weight_int_fullint_float16_quant.py
What are some alternatives?
openpilot - openpilot is an open source driver assistance system. openpilot performs the functions of Automated Lane Centering and Adaptive Cruise Control for 250+ supported car makes and models.
YOLOX - YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/
ncnn - ncnn is a high-performance neural network inference framework optimized for the mobile platform
RobustVideoMatting - Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX, CoreML!
models - Models and examples built with TensorFlow
edgetpu - Coral issue tracker (and legacy Edge TPU API source)
pwnagotchi - (⌐■_■) - Deep Reinforcement Learning instrumenting bettercap for WiFi pwning.
deepsparse - Sparsity-aware deep learning inference runtime for CPUs
PlotNeuralNet - Latex code for making neural networks diagrams
tensorflow-onnx - Convert TensorFlow, Keras, Tensorflow.js and Tflite models to ONNX
onnx-tensorflow - Tensorflow Backend for ONNX
TensorFlow-object-detection-tutorial - The purpose of this tutorial is to learn how to install and prepare TensorFlow framework to train your own convolutional neural network object detection classifier for multiple objects, starting from scratch