Remove extraneous file from repository, keep local only

.gitignore

@@ -36,3 +36,6 @@ test_images/
 # Results files
 results*.txt
 sample_results.txt
+
+# Claude Code instructions (local only)
+CLAUDE.md

CLAUDE.md

@@ -1,53 +0,0 @@
-# CLAUDE.md
-
-This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
-
-## Project Overview
-
-Logo detection system using deep learning models:
-- **DETR** (DEtection TRansformer) for logo region detection
-- **CLIP** (Contrastive Language-Image Pre-training) for feature extraction and matching
-
-## Development Commands
-
-```bash
-# Install dependencies (uses uv package manager)
-uv sync
-
-# Run main script
-uv run python main.py
-
-# Run logo detection module directly
-uv run python logo_detection_detr.py
-```
-
-## Architecture
-
-### Core Module: `logo_detection_detr.py`
-
-The `DetectLogosDETR` class provides the main detection pipeline:
-
-1. **Detection Flow**: OpenCV image (BGR) → DETR detects bounding boxes → CLIP extracts embeddings for each region
-2. **Matching Flow**: Compare detected embeddings against reference logo embeddings using cosine similarity
-
-**Key Methods:**
-- `detect(image)` - Detect logos, returns boxes + CLIP embeddings
-- `get_embedding(image)` - Get CLIP embedding for a reference logo
-- `compare_embeddings(emb1, emb2)` - Cosine similarity between embeddings
-- `detect_and_match(image, references, threshold)` - Combined detection and matching
-
-### Model Configuration
-
-Models are resolved in this order:
-1. Absolute path if provided
-2. Local directory from environment variables (`LOGO_DETR_MODEL_DIR`, `LOGO_CLIP_MODEL_DIR`)
-3. Default local paths: `models/logo_detection/detr`, `models/logo_detection/clip`
-4. HuggingFace download as fallback
-
-Default models:
-- DETR: `Pravallika6/detr-finetuned-logo-detection_v2`
-- CLIP: `openai/clip-vit-large-patch14`
-
-### Reference Dataset
-
-`LogoDet-3K/` contains logo images organized by category: Clothes, Electronic, Food, Leisure, Medical, Necessities, Others, Sports, Transportation.