Spaces:
Running
on
T4
Running
on
T4
| #!/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. | |
| from typing import TYPE_CHECKING | |
| from ..models.auto import AutoModelForVision2Seq | |
| from ..utils import requires_backends | |
| from .base import PipelineTool | |
| if TYPE_CHECKING: | |
| from PIL import Image | |
| class ImageCaptioningTool(PipelineTool): | |
| default_checkpoint = "Salesforce/blip-image-captioning-base" | |
| description = ( | |
| "This is a tool that generates a description of an image. It takes an input named `image` which should be the " | |
| "image to caption, and returns a text that contains the description in English." | |
| ) | |
| name = "image_captioner" | |
| model_class = AutoModelForVision2Seq | |
| inputs = ["image"] | |
| outputs = ["text"] | |
| def __init__(self, *args, **kwargs): | |
| requires_backends(self, ["vision"]) | |
| super().__init__(*args, **kwargs) | |
| def encode(self, image: "Image"): | |
| return self.pre_processor(images=image, return_tensors="pt") | |
| def forward(self, inputs): | |
| return self.model.generate(**inputs) | |
| def decode(self, outputs): | |
| return self.pre_processor.batch_decode(outputs, skip_special_tokens=True)[0].strip() | |