Instructions to use feyninc/multimatte with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- nobg
How to use feyninc/multimatte with nobg:
pip install nobg
# Option 1: use via the predict method from nobg import AutoModel, AutoProcessor model = AutoModel.from_pretrained("feyninc/multimatte").eval() processor = AutoProcessor.from_pretrained("feyninc/multimatte") cutout = model.predict(processor, "image.jpg", "prompt")# Option 2: use the model and processor directly import torch from loadimg import load_img from nobg import AutoModel, AutoProcessor model = AutoModel.from_pretrained("feyninc/multimatte").eval() processor = AutoProcessor.from_pretrained("feyninc/multimatte") image = load_img("image.jpg").convert("RGB") inputs = processor(image, return_tensors="pt") with torch.no_grad(): outputs = model(pixel_values=inputs["pixel_values"]) alpha = processor.post_process_alpha_matting(outputs, target_sizes=[(image.height, image.width)])[0] processor.cutout(image, alpha).save("output.png") - Notebooks
- Google Colab
- Kaggle
Upload processor
Browse files- processor_config.json +34 -0
- tokenizer.json +0 -0
- tokenizer_config.json +17 -0
processor_config.json
ADDED
|
@@ -0,0 +1,34 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"default_prompt": "the main foreground subject",
|
| 3 |
+
"image_processor": {
|
| 4 |
+
"data_format": "channels_first",
|
| 5 |
+
"do_convert_rgb": true,
|
| 6 |
+
"do_normalize": true,
|
| 7 |
+
"do_rescale": true,
|
| 8 |
+
"do_resize": true,
|
| 9 |
+
"image_mean": [
|
| 10 |
+
0.5,
|
| 11 |
+
0.5,
|
| 12 |
+
0.5
|
| 13 |
+
],
|
| 14 |
+
"image_processor_type": "Sam3ImageProcessor",
|
| 15 |
+
"image_std": [
|
| 16 |
+
0.5,
|
| 17 |
+
0.5,
|
| 18 |
+
0.5
|
| 19 |
+
],
|
| 20 |
+
"mask_size": {
|
| 21 |
+
"height": 288,
|
| 22 |
+
"width": 288
|
| 23 |
+
},
|
| 24 |
+
"resample": 2,
|
| 25 |
+
"rescale_factor": 0.00392156862745098,
|
| 26 |
+
"size": {
|
| 27 |
+
"height": 1008,
|
| 28 |
+
"width": 1008
|
| 29 |
+
}
|
| 30 |
+
},
|
| 31 |
+
"point_pad_value": -10,
|
| 32 |
+
"processor_class": "Sam3Processor",
|
| 33 |
+
"target_size": 1008
|
| 34 |
+
}
|
tokenizer.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,17 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 3 |
+
"backend": "tokenizers",
|
| 4 |
+
"bos_token": "<|startoftext|>",
|
| 5 |
+
"clean_up_tokenization_spaces": false,
|
| 6 |
+
"do_lower_case": true,
|
| 7 |
+
"eos_token": "<|endoftext|>",
|
| 8 |
+
"errors": "replace",
|
| 9 |
+
"is_local": false,
|
| 10 |
+
"local_files_only": false,
|
| 11 |
+
"max_length": 32,
|
| 12 |
+
"model_max_length": 32,
|
| 13 |
+
"pad_token": "<|endoftext|>",
|
| 14 |
+
"processor_class": "Sam3Processor",
|
| 15 |
+
"tokenizer_class": "CLIPTokenizer",
|
| 16 |
+
"unk_token": "<|endoftext|>"
|
| 17 |
+
}
|