CSRNet | ECCV 2020 ) Conditional Sequential Modulation | Computer Vision library

by hejingwenhejingwen Python Version: Current License: No License

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kandi X-RAY | CSRNet Summary

CSRNet is a Python library typically used in Artificial Intelligence, Computer Vision, Deep Learning applications. CSRNet has no bugs, it has no vulnerabilities and it has low support. However CSRNet build file is not available. You can download it from GitHub.

(ECCV 2020) Conditional Sequential Modulation for Efficient Global Image Retouching

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Support

CSRNet has a low active ecosystem.

It has 38 star(s) with 7 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

There are 2 open issues and 1 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of CSRNet is current.

Quality

CSRNet has no bugs reported.

Security

CSRNet has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

CSRNet does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

CSRNet releases are not available. You will need to build from source code and install.

CSRNet has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions, examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed CSRNet and discovered the below as its top functions. This is intended to give you an instant insight into CSRNet implemented functionality, and help decide if they suit your requirements.

Resize an image
Calculate the indices of the weights
Cubic cubic cubic cubic cubic
Perform a forward pass through the network
Denormalize a tensor
Normalize x
Print the network representation of the network
Get description of network
Generate MODIC files
Resize a numpy array
Read image files from path
Calculate the SSP similarity between two images
Create a data loader
Run lmdb
Sets up Vimeo 10k
Configuration for RedS
Extract signle
Define concatenation
Forward convolutional layer
Convert RGB image to YCCr
Forward the convolutional layer
Convolution function
Calculate the flow
Create dataset
Flip forward x4
General image folder

Get all kandi verified functions for this library.

CSRNet Key Features

No Key Features are available at this moment for CSRNet.

CSRNet Examples and Code Snippets

No Code Snippets are available at this moment for CSRNet.

Community Discussions

Trending Discussions on CSRNet

I want to train the CSRNet model on UCF_CC_50 dataset which has total number of images 50. and face a problem like

Custom CoreML output layer that sums multiArray output

What are geometry-adaptive kernels?

QUESTION

I want to train the CSRNet model on UCF_CC_50 dataset which has total number of images 50. and face a problem like

Asked 2021-Jun-05 at 04:47

I want to train the CSRNet model on UCF_CC_50 dataset but occurring this problem

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ANSWER

Answered 2021-Jun-03 at 13:08

You are reading a matfile '...\ground_truth\GT_IMG_1.mat' corresponding to the image '...\IMG_1.jpg'. While you process this data point, you try to access variable 'image_info' stored in the matfile you read. As the error message you got states:

KeyError: 'image_info'

The matfile does not contain this variable, 'image_info'.

to debug, read the matfile and see what are the names of the variables stored there. Notice that naming them is case sensitive.

Source https://stackoverflow.com/questions/67815809

QUESTION

Custom CoreML output layer that sums multiArray output

Asked 2021-Apr-02 at 03:03

Please bear with me. I'm new to CoreML and machine learning. I have a CoreML model that I was able to convert from a research paper implementation that used Caffe. It's a CSRNet, the objective being crowd-counting. After much wrangling, I'm able to load the MLmodel into Python using Coremltools, pre-process an image using Pillow and predict an output. The result is a MultiArray (from a density map), which I've then processed further to derive the actual numerical prediction.

How do I add a custom layer as an output to the model that takes the current output and performs the following functionality? I've read numerous articles, and am still at a loss. (Essentially, it sums the values all the values in the MultiArray) I'd like to be able to save the model/ layer and import it into Xcode so that the MLModel result is a single numerical value, and not a MultiArray.

This is the code I'm currently using to convert the output from the model into a number (in Python):

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ANSWER

Answered 2021-Apr-01 at 10:21

You can add a ReduceSumLayerParams to the end of the model. You'll need to do this in Python by hand. If you set its reduceAll parameter to true, it will compute the sum over the entire tensor.

However, in my opinion, it's just as easy to use the model as-is, and in your Swift code grab a pointer to the MLMultiArray's data and use vDSP.sum(a) to compute the sum.

Source https://stackoverflow.com/questions/66898082

QUESTION

What are geometry-adaptive kernels?

Asked 2019-Oct-16 at 06:45

I was reading a paper "CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes" and found this term but couldn't find the exact meaning of geometry-adaptive kernels.Can someone please explain me this?

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ANSWER

Answered 2019-Oct-16 at 06:45

Geometric algorithms are based on geometric objects such as points, lines and circles. The term kernel refers to a collection of representations for constant-size geometric objects and operations on these representations. The term adaptive kernel, in a broad sense, means that these representations are not immutable or fixed, but rather that they can vary according to some criteria.

Source https://stackoverflow.com/questions/58406697

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install CSRNet

Python 3 (Recommend to use Anaconda)
PyTorch >= 1.0
NVIDIA GPU + CUDA
Python packages: pip install numpy opencv-python lmdb pyyaml
TensorBoard: PyTorch >= 1.1: pip install tb-nightly future PyTorch == 1.0: pip install tensorboardX

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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