models
fastbook
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models | fastbook | |
---|---|---|
96 | 23 | |
76,598 | 20,711 | |
0.2% | 1.8% | |
9.5 | 2.6 | |
2 days ago | 13 days ago | |
Python | Jupyter Notebook | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
models
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Changing box prediction head on SSD from TF2 model zoo
I am using SSD ResNet50 V1 FPN 1024x1024 (RetinaNet50) from TF model zoo .
- Labeling question
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I'm looking for article for object detection explanation with working code
I spent some time looking for an article that explains object detection, but it seems that there are a lot of articles out there that are not very helpful. Some of these articles focus on specific things like mAP or UoI, but without the broader context, they are not very useful. The main issue with these articles is that they either don't provide any code, or they give examples that are not very helpful, like terminal commands to download a framework and train a model. I started from this link https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/tf2.md, but it id not very useful. What I really need is a comprehensive explanation of how object detection works, along with working code that I can use to see the results for myself. I know that there are many different approaches to object localization, such as one-stage or two-stage detection, Faster R-CNN, or SSD, but I don't really care which approach will be described. I just need a starting point with clear explanations and working code that I can run.
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good computer vision or deep learning projects in github
TensorFlow Models (GitHub: https://github.com/tensorflow/models) is a collection of diverse TensorFlow-based ML and DL models for tasks like image classification, object detection, and text classification.
- [D] I just realised: GPT-4 with image input can interpret any computer screen, any userinterface and any combination of them.
- [D]Custom Trained Networks for EasyOCR
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Has anyone tried reverse engineering Google Tensor's AI-specific instruction set?
Assuming you're talking about leveraging the device's the device's Tensor Processing unit for machine learning then there then you're in luck because Google designed the TPU to work extremely well with the machine learning solutions developed by Google such as easy to use SDKs, robust runtimes and APIs ( e.g. - which you probably aren't going to need to touch). If you're a researcher there's plenty of lower level stuff floating about - but developers would be, again, better off staying away from it.
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Tensorflow for M1 macs with GPU support
Thank you so that worked and I was able to install it š . But when I try to run the test script as mentioned here, I get an error ModuleNotFoundError: No module named 'object_detection'. Am I doing something wrong, Iām using a conda environment and I have tensorflow-macos and tensorflow-metal plug-in installed in the same environment as tf-models.
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Object detection API deprecated
I've noticed while implementing tensorflow object detection API for a client that they have deprecated the repo and will not be updating it: https://github.com/tensorflow/models/tree/master/research/object_detection
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NVIDIA's Rip-Off - RTX 4070 Ti Review & Benchmarks
I implore you, download a model from Tensorflowās model repo and try training it on your conventional GPU. See how much your memory bandwidth and memory count will severely bottleneck performance, in addition see how long it takes to get any decent results.
fastbook
- The fastai book, published as Jupyter Notebooks
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fast.ai Book in Rust - Chapter 2 - Part 1
This chapter focuses on defining the DataLoader classes and a Bing Image Search downloader that is provided with the fastai library. We're not going to implement a Bing downloader. That is too much work for something that could be a crate on its own. Please feel free to write such a crate, though, the world could use one.
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Fastai Chapter 4 - The important parts, Part 2: Building a regression model
The book is available online here The course is accessible here
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Need help trying to run Fastai notebooks on kaggle.
Fastai Lesson 2 notebook
- Fast.ai's Practical Deep Learning for Coders Has Been Updated
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How can i as 15 years old start learning machine learning, i watched some python courses on youtube but it covered the basics and I want to go more in depth. Are there any books, online courses, etc.. I cant really pay for anything so no paid courses. Thank you
I recently read the FastAI book from O'Reilly, which is also published as a series of notebooks on GitHub here. I personally liked it because it shows how to obtain a working model trained with modern techniques without delving too much in the low-level details.
- [D] Recommendation of books to achieve a deeper knowledge of the field
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I recently got a bit of money from my grandparents to get myself a present and I wanted to get a good Python book. Which book would you recommend?
I recommend fastai-fastbook. I just started myself though itās a coupled with tools and a way of working that may help you including being and to create and publish python packages from a jupyter notebook using nbdev
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āPerceptronā paved the way for AI 60 years too soon (2019)
The fastai book actually makes a nice comparison between the systems described in PDP and modern deep learning.
> In fact, the approach laid out in PDP is very similar to the approach used in today's neural networks.
From: https://github.com/fastai/fastbook/blob/master/01_intro.ipyn...
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Starting a career as a Python developer
Iām a fan of fast book by fastai.
What are some alternatives?
netron - Visualizer for neural network, deep learning and machine learning models
fastai - The fastai deep learning library
SSD-Mobilenet-Custom-Object-Detector-Model-using-Tensorflow-2 - This repository contains the script and process to create custom SSD Mobilenet model for object detection
CLIP - CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
onnx-tensorflow - Tensorflow Backend for ONNX
Franklin.jl - (yet another) static site generator. Simple, customisable, fast, maths with KaTeX, code evaluation, optional pre-rendering, in Julia.
redisai-examples - RedisAI showcase
car-damage-detection - Detectron2 for car damage detection using custom dataset
labelImg - LabelImg is now part of the Label Studio community. The popular image annotation tool created by Tzutalin is no longer actively being developed, but you can check out Label Studio, the open source data labeling tool for images, text, hypertext, audio, video and time-series data.
Hands-On-Deep-Learning-Algorithms-with-Python - Hands-On Deep Learning Algorithms with Python, By Packt
tensorboard - TensorFlow's Visualization Toolkit
articulated-animation - Code for Motion Representations for Articulated Animation paper