README.md

metadata

title: SAM3 Detection Browser
emoji: 🔍
colorFrom: blue
colorTo: green
sdk: static
pinned: false
models:
  - facebook/sam3

🔍 SAM3 Object Detection Browser

A simple, interactive web application for browsing and exploring object detection results from Meta's SAM3 (Segment Anything Model 3).

Features

• Visual Detection Display: View images with bounding boxes overlaid on detected objects
• Confidence Filtering: Adjust confidence threshold with a slider to filter detections
• Statistics Dashboard: See overall detection statistics including:
  • Total filtered images
  • Images with detections
  • Total detections
  • Average detections per image
• Flexible Navigation: Browse through datasets with pagination
• Real-time Updates: Filters update visualization instantly
• Color-coded Confidence: Bounding boxes and scores are color-coded:
  • 🟢 Green: High confidence (≥70%)
  • 🟠 Orange: Medium confidence (40-70%)
  • 🔴 Red: Low confidence (<40%)

How to Use

1. Enter a Dataset ID: Input any HuggingFace dataset that contains object detection results from SAM3

   • Default: davanstrien/newspapers-image-predictions
   • Format: username/dataset-name

2. Select Split: Choose which dataset split to view (train/validation/test)

3. Adjust Filters:

   • Move the confidence slider to filter detections by minimum confidence score
   • Check "Show only images with detections" to hide images without any detected objects

4. Browse: Navigate through pages using Previous/Next buttons

Dataset Requirements

This browser works with any HuggingFace dataset that has:

• An image column containing images
• An objects column with the structure:

  {
      "bbox": [[x, y, width, height], ...],    # Bounding box coordinates
      "category": [0, 0, ...],                  # Category indices
      "score": [0.8, 0.6, ...]                  # Confidence scores
  }
  

This matches the output format from the detect-objects.py script.

Example Datasets

• davanstrien/newspapers-image-predictions - Photograph detections in historical newspapers

Creating Your Own Detection Dataset

Use the SAM3 detection script to create your own datasets:

# Detect objects in your images
uv run https://huggingface.co/datasets/uv-scripts/sam3/raw/main/detect-objects.py \
    your-dataset \
    your-output-dataset \
    --class-name "photograph" \
    --confidence-threshold 0.5

Then view the results by entering your-output-dataset in this browser!

Technical Details

• Technology: Pure HTML/CSS/JavaScript (no backend required)
• Data Source: HuggingFace Datasets API (parquet endpoint)
• Rendering: HTML5 Canvas for bounding box overlays
• Performance: Loads 12 images per page for optimal performance

Related Projects

• SAM3 Detection Script - Create detection datasets
• SAM3 Model - The base model
• UV Scripts Organization - More ready-to-run ML scripts

License

MIT License - Feel free to use and modify for your own projects!