DPED | trained models for automatic photo quality enhancement | Machine Learning library
kandi X-RAY | DPED Summary
kandi X-RAY | DPED Summary
Software and pre-trained models for automatic photo quality enhancement using Deep Convolutional Networks
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Top functions reviewed by kandi - BETA
- Convolution layer
- Pool layer
- Layer convolution layer
- Creates leaky_relu
- ResNet residuals
- Instance normalization
- Create a bias variable
- 2d conv layer
- Compute SSIM for multiple images
- Calculates the specialGauss - Gaussian distribution
- Solve the SSIM between two images
- Blurb a tensor
- Generates a Gaussian kernel
- Parse command line arguments
- Return the size of a tensor
- Determine the resolution for a specific resolution
- Logarithm of x
- Load test data
- Extract crop
- Returns a dictionary of all available resolution sizes
- Computes adversarial layer
- Load training image
- Process test_model arguments
- Preprocess an image
DPED Key Features
DPED Examples and Code Snippets
Lines of Code : 30
License : No License
Copy├── data
│ ├── dped -> /home/***/datasets/dped/
│ ├── __init__.py
│ ├── load_dataset.py
│ └── pretrain_models
├── demo
├── experiments
│ ├── config
│ └── logs
├── loss
│ python train_model.py model=
python train_model.py model=iphone batch_size=50 dped_dir=dped/ w_color=0.7
python test_model.py model=
python test_model.py model=iphone_orig test_subset=full resolution=orig use_gpu=true
python test_model.py model=i python train_model.py model=iphone num_train_iters=40000 run=replication convdeconv depth=16
python test_model.py model=iphone_orig test_subset=full resolution=orig use_gpu=true
python test_model.py model=iphone iteration=[40000] test_subset=full r Community Discussions
Trending Discussions on DPED
QUESTION
I followed these instructions
Specifically, I want to run a downloaded Tensorflow model from Github. I only have an Intel GPU on my computer, so I want to execute the Tensorflow model on my CPU. As described here on GitHub, it should be possible by setting the use-gpu parameter to false. So I run this command:
...ANSWER
Answered 2019-Jul-25 at 21:41there are two module of tensorlfow:'tensorflow','tensorflow-gpu'
on cpu you need to install tensorlfow with pip install tensorflow or on conda conda install tensorflow
EDIT for second question:
If a TensorFlow operation is placed on the GPU, then the execution engine must have the GPU implementation of that operation, known as the kernel.
If the kernel is not present, then the placement results in a runtime error. Also, if the requested GPU device does not exist, then a runtime error is raised.
The best way to handle is to allow the operation to be placed on the CPU if requesting the GPU device results in an error.
One answer would be to remove all GPU configs and second would be soft placement if GPU is not found as explained above use config.allow_soft_placement = True
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install DPED
You can use DPED like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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