uv-scripts/sam3-detection-browser

🔍 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. 1.Enter a Dataset ID: Input any HuggingFace dataset that contains object detection results from SAM3
2. 2.Default: davanstrien/newspapers-image-predictions
3. 3.Format: username/dataset-name

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

1. 1.Adjust Filters:
2. 2.Move the confidence slider to filter detections by minimum confidence score
3. 3.Check "Show only images with detections" to hide images without any detected objects

1. 1.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!