tejas-label-ocr

Lightweight, stateless Python library for extracting structured data from product packaging labels using OCR and LLM-based parsing.

—

Features

Stateless & In-Memory: Processes raw image bytes—no disk I/O, ideal for serverless (FastAPI/Flask).
OCR + LLM Powered: Uses PaddleOCR for text extraction and Mistral AI (mistral-small-latest) for structured parsing.
Noise Filtering: Automatically cleans low-confidence OCR text and groups spatial blocks (rows/columns/proximity).
Flexible Auth: Pass api_key directly or via MISTRAL_API_KEY environment variable.
Structured JSON Output: Extracts brand, product name, ingredients, nutrition facts, allergens, and more.

—

Installation

pip install tejas-label-ocr

—

Usage

Front Label Processing

from label_ocr import process_front_label

with open("product_label.jpg", "rb") as f:
    image_bytes = f.read()

result = process_front_label(image_bytes, api_key="your-mistral-api-key")
print(result)
# Output: {"brand": "Nestlé", "product_name": "Organic Oats", "claims": ["Gluten-Free", "Non-GMO"], ...}

Nutrition Label Processing

from label_ocr import process_nutrition_label

with open("nutrition_panel.jpg", "rb") as f:
    image_bytes = f.read()

result = process_nutrition_label(image_bytes, api_key="your-mistral-api-key")
print(result)
# Output: {"serving_size": "30g", "nutrients": [{"name": "Calories", "value": 120, "unit": "kcal", "%RDA": 6}], ...}

— Notes —–

Requires a Mistral AI API key (sign up at Mistral AI).
For best results, use high-resolution images of labels with clear text.

Metadata

Release files for tejas-label-ocr 0.1.9

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for tejas-label-ocr 0.1.9
File	Size	Uploaded
tejas_label_ocr-0.1.9.tar.gz	8.1 kB	Aug 5, 2026	Details

Built distribution (wheel)

Table of built distributions (wheels) for tejas-label-ocr 0.1.9
File	Interpreter	ABI	Platform	Reset
tejas_label_ocr-0.1.9-py3-none-any.whl 8.4 kB Aug 5, 2026	Python 3	none	any	Details

Total release size: 16.5 kB

Release files / tejas_label_ocr-0.1.9.tar.gz

Download URL	tejas_label_ocr-0.1.9.tar.gz
Size	8.1 kB
Tags	Source
SHA-256 checksum How to use checksums	`e5080ceb6e8ba9c1ec21d3123d59113cfbe799ebdaf68e78e135228fd5935895`
BLAKE2b-256 checksum How to use checksums	`dca34b5df4f2ad85cb2cdab033fa17f91fbd7408e53049a59415b82c9ae87e13`
Upload date	Aug 5, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/7.0.0 CPython/3.12.9`

Release files / tejas_label_ocr-0.1.9-py3-none-any.whl

Download URL	tejas_label_ocr-0.1.9-py3-none-any.whl
Size	8.4 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`e880fb2813cf17db0850e734a453f1540c067b063225ba3a633ea67d4f9d78bc`
BLAKE2b-256 checksum How to use checksums	`27f96e8d3acb093f8f52ef51fb6b6c75d09632f2171e3151fbe35b0315c30c60`
Upload date	Aug 5, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/7.0.0 CPython/3.12.9`