procslib 0.4.2

Multi-purpose processing library for downstream use

procslib

Multi-purpose processing library for various inference tasks.
Generated with copier-uv.

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Installation

pip install procslib

Or using uv:

uv tool install procslib

Quick Usage

Below is a minimal example of how to infer images with procslib:

from procslib import get_model_keys, get_model

# List available models
print(get_model_keys())

# Create a model, e.g. "twitter_logfav"
model = get_model("twitter_logfav")

# Infer on some images
image_paths = ["path/to/image1.jpg", "path/to/image2.jpg"]
results_df = model.infer_many(image_paths)
print(results_df.head())

Supported Models

You can retrieve a model via get_model(key). Here’s a quick reference:

Key	Description
twitter_logfav	A model predicting Twitter favorites (log-scaled) for anime images
weakm_v2	A previous version of numeric aesthetics scoring (anime)
siglip_aesthetic	A Siglip-based aesthetic model for general images (requires a newer transformers)
pixiv_compound_score	A numeric aesthetics score model trained on pixiv data
cv2_metrics	Basic image metrics (noise, exposure, clarity, edge count, etc.) (No GPU usage)
complexity_ic9600	A complexity-measuring model for images
rtmpose	Detects body parts in images (RTMDet-based)
depth	MiDaS-based depth estimation (returns a “depthness” metric)
q_align_quality	Q-Align model for quality assessment (requires transformers==4.36.1)
q_align_aesthetics	Q-Align model for aesthetics (also needs that older transformers)
laion_watermark	A fast watermark (text detection) model from LAION
clip_aesthetic	Caches CLIP embeddings and calculates aesthetic scores and 0-shot classifications from embeddings

Note: Q-Align and Siglip Aesthetics are incompatible with each other’s transformers version. If you need both, see Docs: Handling Conflicting Dependencies.

Development

For development tasks (testing, formatting, releasing), see Dev Guide or run:

make setup   # one-time
make format  # auto-format
make test
make check
make changelog
make release version=x.y.z

Documentation

To learn more, visit our MkDocs-based docs or run:

make docs host=0.0.0.0

• Quick Start: Using Models
• Quick Start: Adding New Models
• VSCode Tips