Initial commit: Logo detection test framework

Add DETR+CLIP based logo detection library and test framework:
- DetectLogosDETR class for logo detection and matching
- Test script with margin-based and multi-ref matching methods
- Data preparation script for test database
- Documentation for API usage and test methodology

CLAUDE.md

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+# 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.