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| #!/usr/bin/env python | |
| # coding=utf-8 | |
| # Copyright 2023 The HuggingFace Inc. team. All rights reserved. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| import numpy as np | |
| import torch | |
| from ..models.clipseg import CLIPSegForImageSegmentation | |
| from ..utils import is_vision_available, requires_backends | |
| from .base import PipelineTool | |
| if is_vision_available(): | |
| from PIL import Image | |
| class ImageSegmentationTool(PipelineTool): | |
| description = ( | |
| "This is a tool that creates a segmentation mask of an image according to a label. It cannot create an image." | |
| "It takes two arguments named `image` which should be the original image, and `label` which should be a text " | |
| "describing the elements what should be identified in the segmentation mask. The tool returns the mask." | |
| ) | |
| default_checkpoint = "CIDAS/clipseg-rd64-refined" | |
| name = "image_segmenter" | |
| model_class = CLIPSegForImageSegmentation | |
| inputs = ["image", "text"] | |
| outputs = ["image"] | |
| def __init__(self, *args, **kwargs): | |
| requires_backends(self, ["vision"]) | |
| super().__init__(*args, **kwargs) | |
| def encode(self, image: "Image", label: str): | |
| return self.pre_processor(text=[label], images=[image], padding=True, return_tensors="pt") | |
| def forward(self, inputs): | |
| with torch.no_grad(): | |
| logits = self.model(**inputs).logits | |
| return logits | |
| def decode(self, outputs): | |
| array = outputs.cpu().detach().numpy() | |
| array[array <= 0] = 0 | |
| array[array > 0] = 1 | |
| return Image.fromarray((array * 255).astype(np.uint8)) | |