about training data
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- Dominant language
- Python
- Stars
- 275
- Forks
- 46
- PR merge metrics
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Description
您的文中说：
“we choose the 10s and 30s
long-exposure subset captured by the Sony α7s II camera, and manually take
out those with visible noise, leaving 214 high quality RAW images”
“According to our noise model described in Section 3, if clean RAW images
were available, we can synthesize noisy images by sampling from a PoissonGaussian distribution with estimated noise parameters measured from the target
sensor.
”
现在能找到的只有曝光10s和30s的SONY数据集中的clean raw图，他们的ISO是可以知道的
但是添加噪声的输入图需要自己制作，这需要制作一个包含ISO的json文件，这有点麻烦
可以分享您的添加噪声的数据的制作代码 和 包含训练raw图参数（如ISO等）的json文件吗
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reading the repository documentation and the Section 3 noise-model description referenced in the issue, then locate any existing training-data or noise-synthesis entry points. Done means providing the requested noise-data generation code and a JSON file containing the training RAW image parameters, including ISO values.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data, machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100