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README.md

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+---
+license: cc-by-nc-4.0
+library_name: coreml
+pipeline_tag: image-segmentation
+tags:
+  - background-removal
+  - image-segmentation
+  - coreml
+  - apple-neural-engine
+  - birefnet
+  - rmbg
+language:
+  - en
+base_model: briaai/RMBG-2.0
+---
+
+# RMBG-2 CoreML - Background Removal Model
+
+CoreML conversion of [BRIA AI's RMBG-2.0](https://huggingface.co/briaai/RMBG-2.0) background removal model, optimized for Apple Neural Engine (ANE).
+
+## Model Description
+
+This is a native ML Program format CoreML model converted from RMBG-2.0 (BiRefNet architecture) for high-quality background removal on Apple devices.
+
+### Key Features
+
+- **Native CoreML ML Program format** - Full ANE compatibility
+- **No custom layers** - Uses only native CoreML operations
+- **1024x1024 input resolution** - High-quality segmentation
+- **Fast inference** - ~3 seconds on Apple Silicon with ANE
+
+## Usage
+
+### With RMBG2Swift Package
+
+```swift
+import RMBG2Swift
+
+// Simple one-liner
+let rmbg = try await RMBG2()
+let result = try await rmbg.removeBackground(from: image)
+
+// Access the result
+let outputImage = result.image  // Image with transparent background
+let mask = result.mask          // Grayscale segmentation mask
+```
+
+**Swift Package:** [github.com/VincentGourbin/RMBG2Swift](https://github.com/VincentGourbin/RMBG2Swift)
+
+### Manual Integration
+
+```swift
+import CoreML
+
+// Load the model
+let config = MLModelConfiguration()
+config.computeUnits = .all  // Enable ANE
+
+let model = try await MLModel.load(contentsOf: modelURL, configuration: config)
+
+// Prepare input (1024x1024, NCHW format with ImageNet normalization)
+let input = MLDictionaryFeatureProvider(dictionary: ["input": inputArray])
+
+// Run inference
+let output = try model.prediction(from: input)
+
+// Get mask from output_3 (full resolution)
+let mask = output.featureValue(for: "output_3")?.multiArrayValue
+```
+
+## Model Details
+
+| Property | Value |
+|----------|-------|
+| Architecture | BiRefNet |
+| Input Size | 1024 x 1024 |
+| Input Format | RGB, NCHW [1, 3, 1024, 1024] |
+| Normalization | ImageNet (mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) |
+| Output | 4 scales (output_0 to output_3), use output_3 for full resolution |
+| Format | ML Program (.mlpackage) |
+| Minimum OS | macOS 13+ / iOS 16+ |
+| Compute Units | All (CPU, GPU, ANE) |
+
+## Performance
+
+Tested on Apple Silicon:
+
+| Device | Inference Time |
+|--------|---------------|
+| M1 Pro (ANE) | ~3s |
+| M1 Pro (GPU) | ~5s |
+
+## Files
+
+- `RMBG-2-native.mlpackage/` - CoreML ML Program model
+
+## License
+
+**Creative Commons Attribution-NonCommercial 4.0 (CC BY-NC 4.0)**
+
+- **Free for non-commercial use**: Research, personal projects, education
+- **Commercial use requires a separate license** from BRIA AI
+
+For commercial licensing, contact: [bria.ai/contact-us](https://bria.ai/contact-us)
+
+## Attribution
+
+This CoreML conversion is based on the RMBG-2.0 model by BRIA AI:
+
+- **Original Model**: [briaai/RMBG-2.0](https://huggingface.co/briaai/RMBG-2.0)
+- **Architecture**: BiRefNet
+- **Creator**: [BRIA AI](https://bria.ai)
+
+## Related Links
+
+- [RMBG2Swift - Swift Package](https://github.com/VincentGourbin/RMBG2Swift)
+- [Original RMBG-2.0 Model](https://huggingface.co/briaai/RMBG-2.0)
+- [BiRefNet Paper](https://github.com/ZhengPeng7/BiRefNet)

RMBG-2-native.mlpackage/Data/com.apple.CoreML/model.mlmodel

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+size 3188148

RMBG-2-native.mlpackage/Data/com.apple.CoreML/weights/weight.bin

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RMBG-2-native.mlpackage/Manifest.json

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+{
+    "fileFormatVersion": "1.0.0",
+    "itemInfoEntries": {
+        "19571D65-9D4F-446B-8F53-D1804442FDF4": {
+            "author": "com.apple.CoreML",
+            "description": "CoreML Model Specification",
+            "name": "model.mlmodel",
+            "path": "com.apple.CoreML/model.mlmodel"
+        },
+        "BE5CBAF5-BDF3-4E72-A73C-2F4D5EBCE60F": {
+            "author": "com.apple.CoreML",
+            "description": "CoreML Model Weights",
+            "name": "weights",
+            "path": "com.apple.CoreML/weights"
+        }
+    },
+    "rootModelIdentifier": "19571D65-9D4F-446B-8F53-D1804442FDF4"
+}

config.json

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+{
+  "model_type": "RMBG-2-CoreML",
+  "architecture": "BiRefNet",
+  "input_size": 1024,
+  "input_format": "NCHW",
+  "input_channels": 3,
+  "normalization": {
+    "mean": [0.485, 0.456, 0.406],
+    "std": [0.229, 0.224, 0.225]
+  },
+  "outputs": ["output_0", "output_1", "output_2", "output_3"],
+  "primary_output": "output_3",
+  "format": "mlpackage",
+  "compute_units": "all",
+  "minimum_deployment_target": {
+    "macOS": "13.0",
+    "iOS": "16.0"
+  },
+  "original_model": "briaai/RMBG-2.0",
+  "license": "CC-BY-NC-4.0",
+  "version": "1.0.0"
+}