RankIQA.PyTorch: Image Quality Assessment
RankIQA.PyTorch is a PyTorch-based model for evaluating the quality of images
- •When you need to assess the quality of a large number of images automatically
- •When you want to compare the performance of different image processing algorithms
- •When you need to filter out low-quality images from a dataset
python test.py -d /path/to/your/test/images -m models/RankIQA.pth
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Expect 20–40 minutes in a terminal — or let your AI agent drive it.
mkdir -p ~/.claude/skills/rankiqa-pytorch && curl -fsSL https://workflowstacks.com/api/skills/rankiqa-pytorch/claude-skill -o ~/.claude/skills/rankiqa-pytorch/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
RankIQA.PyTorch: Image Quality Assessment is a medium Python project (~3.2k lines across 46 code files). Expect some technical setup — comfortable with a terminal, or ask a developer. Last commit 76 months ago, no license file, no tests found.
- 1README.mdStart here — what it does and how to install it
- 2main.pyWhere the program starts running
- 3requirements.txtDependencies and the commands it exposes
- 4demos/__init__.pyA worked example — copy this to get going
Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.
Expect 20–40 minutes in a terminal — or let your AI agent drive it.
mkdir -p ~/.claude/skills/rankiqa-pytorch && curl -fsSL https://workflowstacks.com/api/skills/rankiqa-pytorch/claude-skill -o ~/.claude/skills/rankiqa-pytorch/SKILL.mdOpens the app with this repo with the prompt ready to go — no copy-paste needed.
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