https://github.com/tohrusky/srmd-ncnn-py
Python Binding for srmd-ncnn-vulkan with PyBind11
https://github.com/tohrusky/srmd-ncnn-py
cpp ncnn pybind11 python3 srmd super-resolution
Last synced: 10 months ago
JSON representation
Python Binding for srmd-ncnn-vulkan with PyBind11
- Host: GitHub
- URL: https://github.com/tohrusky/srmd-ncnn-py
- Owner: Tohrusky
- License: bsd-3-clause
- Created: 2023-04-21T03:56:16.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2023-12-30T10:59:40.000Z (over 2 years ago)
- Last Synced: 2025-07-10T10:54:21.461Z (11 months ago)
- Topics: cpp, ncnn, pybind11, python3, srmd, super-resolution
- Language: C++
- Homepage:
- Size: 16.8 MB
- Stars: 3
- Watchers: 2
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# srmd-ncnn-py
Python Binding for srmd-ncnn-py with PyBind11
[](https://badge.fury.io/py/srmd-ncnn-py?123456)
[](https://github.com/Tohrusky/srmd-ncnn-py/actions/workflows/Release.yml)
SRMD - Learning a Single Convolutional Super-Resolution Network for Multiple Degradations (CVPR, 2018).
This wrapper provides an easy-to-use interface for running the pre-trained SRMD model.
### Current building status matrix
| System | Status | CPU (32bit) | CPU (64bit) | GPU (32bit) | GPU (64bit) |
| :-----------: | :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :---------: | :---------: | :---------: | :----------------: |
| Linux (Clang) | [](https://github.com/Tohrusky/srmd-ncnn-py/actions/workflows/CI-Linux-x64-Clang.yml) | — | — | — | :white_check_mark: |
| Linux (GCC) | [](https://github.com/Tohrusky/srmd-ncnn-py/actions/workflows/CI-Linux-x64-GCC.yml) | — | — | — | :white_check_mark: |
| Windows | [](https://github.com/Tohrusky/srmd-ncnn-py/actions/workflows/CI-Windows-x64-MSVC.yml) | — | — | — | :white_check_mark: |
| MacOS | [](https://github.com/Tohrusky/srmd-ncnn-py/actions/workflows/CI-MacOS-Universal-Clang.yml) | — | — | — | :white_check_mark: |
| MacOS (ARM) | [](https://github.com/Tohrusky/srmd-ncnn-py/actions/workflows/CI-MacOS-Universal-Clang.yml) | — | — | — | :white_check_mark: |
# Usage
`Python >= 3.6 (>= 3.9 in MacOS arm)`
To use this package, simply install it via pip:
```sh
pip install srmd-ncnn-py
```
For Linux user:
```sh
apt install -y libomp5 libvulkan-dev
```
Then, import the SRMD class from the package:
```python
from srmd_ncnn_py import SRMD
```
To initialize the model:
```python
srmd = SRMD(gpuid: int = 0, tta_mode: bool = False, noise: int = 3, scale: int = 2, tilesize: int = 0, model: int = 0)
# model can be "models-srmd" or an absolute path to a model folder
```
Here, gpuid specifies the GPU device to use, tta_mode enables test-time augmentation, noise specifies the level of noise to apply to the image (-1 to 10), scale is the scaling factor for super-resolution (2 to 4), tilesize specifies the tile size for processing (0 or >= 32), and model specifies the pre-trained model to use.
Once the model is initialized, you can use the upscale method to super-resolve your images:
### Pillow
```python
from PIL import Image
srmd = SRMD(gpuid=0)
with Image.open("input.jpg") as image:
image = srmd.process_pil(image)
image.save("output.jpg", quality=95)
```
### opencv-python
```python
import cv2
srmd = SRMD(gpuid=0)
image = cv2.imdecode(np.fromfile("input.jpg", dtype=np.uint8), cv2.IMREAD_COLOR)
image = srmd.process_cv2(image)
cv2.imencode(".jpg", image)[1].tofile("output_cv2.jpg")
```
### ffmpeg
```python
import subprocess as sp
# your ffmpeg parameters
command_out = [FFMPEG_BIN,........]
command_in = [FFMPEG_BIN,........]
pipe_out = sp.Popen(command_out, stdout=sp.PIPE, bufsize=10 ** 8)
pipe_in = sp.Popen(command_in, stdin=sp.PIPE)
srmd = SRMD(gpuid=0)
while True:
raw_image = pipe_out.stdout.read(src_width * src_height * 3)
if not raw_image:
break
raw_image = srmd.process_bytes(raw_image, src_width, src_height, 3)
pipe_in.stdin.write(raw_image)
```
# Build
[here](https://github.com/Tohrusky/srmd-ncnn-py/blob/main/.github/workflows/Release.yml)
_The project just only been tested in Ubuntu 18+ and Debian 9+ environments on Linux, so if the project does not work on your system, please try building it._
# References
The following references were used in the development of this project:
[nihui/srmd-ncnn-vulkan](https://github.com/nihui/srmd-ncnn-vulkan) - This project was the main inspiration for our work. It provided the core implementation of the SRMD algorithm using the ncnn and Vulkan libraries.
[cszn/SRMD](https://github.com/cszn/SRMD) - Learning a Single Convolutional Super-Resolution Network for Multiple Degradations (CVPR, 2018) (Matlab)
[media2x/srmd-ncnn-vulkan-python](https://github.com/media2x/srmd-ncnn-vulkan-python) - This project was used as a reference for implementing the wrapper. _Special thanks_ to the original author for sharing the code.
[ncnn](https://github.com/Tencent/ncnn) - ncnn is a high-performance neural network inference framework developed by Tencent AI Lab.
# License
This project is licensed under the BSD 3-Clause - see the [LICENSE file](https://github.com/Tohrusky/srmd-ncnn-py/blob/main/LICENSE) for details.