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macromate-exact-fix

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Fixes nutrition data and model loading.

Software Engineering#pytorch#django#ml-fix#nutrition-prediction#efficientnetv2-m#nutrition-database
Authorrenish7606
Version1.0.0
Installs0

System Documentation

What problem does it solve?

MacroMate's nutrition predictor sometimes returns 0 kcal or misleading values because nutrition data is nested under nutrition_data and the model loader uses the wrong architecture, causing dependency on CLIP fallback. This skill provides targeted patches to correct the nutrition extractor, switch the model loader to EfficientNetV2-M, adjust preprocessing, and enable startup verification for reliable nutrition data.

Core Features & Use Cases

  • Nutrition data corrected: read from nutrition_data and normalize calories, protein, carbohydrates, fat, fiber, sugar, vitamins, calcium, and iron.
  • Model loading accuracy: load EfficientNetV2-M with 351 classes and 480x480 input, ensuring predictions are not delegated to CLIP.
  • Startup validation: verify label_nutrition_mapping.json entries at startup and log known foods.

Quick Start

Apply the exact fixes to the MacroMate nutrition predictor to ensure correct nutrition extraction and proper EfficientNetV2-M model loading.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

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Please help me install this Skill:
Name: macromate-exact-fix
Download link: https://github.com/renish7606/MacroMate/archive/main.zip#macromate-exact-fix

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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