tejas-label-ocr

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

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Features

Stateless & In-Memory: Processes raw image bytes—no disk I/O, ideal for serverless (FastAPI/Flask).
OCR + LLM Powered: Uses EasyOCR 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.

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Installation

pip install tejas-label-ocr

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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 0.1.3

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 0.1.3
File	Size	Uploaded
tejas_label_ocr-0.1.3.tar.gz	8.4 kB	Aug 5, 2026	Details

Built distribution (wheel)

Table of built distributions (wheels) for tejas-label-ocr 0.1.3
File	Interpreter	ABI	Platform	Reset
tejas_label_ocr-0.1.3-py3-none-any.whl 9.7 kB Aug 5, 2026	Python 3	none	any	Details

Total release size: 18.1 kB

Release files / tejas_label_ocr-0.1.3.tar.gz

Download URL	tejas_label_ocr-0.1.3.tar.gz
Size	8.4 kB
Tags	Source
SHA-256 checksum How to use checksums	`e3c428a707b0ee2dbb5229df5f43d02a07197339771c1bbcb7e473b1d33322e5`
BLAKE2b-256 checksum How to use checksums	`6a1e14e066c6379a7220e701e97853b4316bce206dd2f257cfab40fc4fc1c801`
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-0.1.3-py3-none-any.whl

Download URL	tejas_label_ocr-0.1.3-py3-none-any.whl
Size	9.7 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`41bb4bd9206ebc07c8bfdc5576e1d176b79e1f55d558709e05d22f4f68af30c7`
BLAKE2b-256 checksum How to use checksums	`6224ca645d3abb42d88ba27239aa180decd068eb0565e7228ffe7283a57bb00a`
Upload date	Aug 5, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/7.0.0 CPython/3.12.9`