Segformer B0 Clothes

🚀 用于衣物分割的微调Segformer B0模型

本项目是基于ATR数据集对SegFormer模型进行微调，以实现衣物分割任务。该数据集在Hugging Face上的名称为 "mattmdjaga/human_parsing_dataset"。

🚀 快速开始

SegFormer模型经过微调，可用于衣物分割任务。以下是使用该模型进行衣物分割的代码示例：

from transformers import SegformerImageProcessor, AutoModelForSemanticSegmentation
from PIL import Image
import requests
import matplotlib.pyplot as plt
import torch.nn as nn

extractor = SegformerImageProcessor.from_pretrained("mattmdjaga/segformer_b0_clothes")
model = AutoModelForSemanticSegmentation.from_pretrained("mattmdjaga/segformer_b0_clothes")

url = "https://plus.unsplash.com/premium_photo-1673210886161-bfcc40f54d1f?ixlib=rb-4.0.3&ixid=MnwxMjA3fDB8MHxzZWFyY2h8MXx8cGVyc29uJTIwc3RhbmRpbmd8ZW58MHx8MHx8&w=1000&q=80"

image = Image.open(requests.get(url, stream=True).raw)
inputs = extractor(images=image, return_tensors="pt")

outputs = model(**inputs)
logits = outputs.logits.cpu()

upsampled_logits = nn.functional.interpolate(
    logits,
    size=image.size[::-1],
    mode="bilinear",
    align_corners=False,
)

pred_seg = upsampled_logits.argmax(dim=1)[0]
plt.imshow(pred_seg)

💻 使用示例

基础用法

from transformers import SegformerImageProcessor, AutoModelForSemanticSegmentation
from PIL import Image
import requests
import matplotlib.pyplot as plt
import torch.nn as nn

extractor = SegformerImageProcessor.from_pretrained("mattmdjaga/segformer_b0_clothes")
model = AutoModelForSemanticSegmentation.from_pretrained("mattmdjaga/segformer_b0_clothes")

url = "https://plus.unsplash.com/premium_photo-1673210886161-bfcc40f54d1f?ixlib=rb-4.0.3&ixid=MnwxMjA3fDB8MHxzZWFyY2h8MXx8cGVyc29uJTIwc3RhbmRpbmd8ZW58MHx8MHx8&w=1000&q=80"

image = Image.open(requests.get(url, stream=True).raw)
inputs = extractor(images=image, return_tensors="pt")

outputs = model(**inputs)
logits = outputs.logits.cpu()

upsampled_logits = nn.functional.interpolate(
    logits,
    size=image.size[::-1],
    mode="bilinear",
    align_corners=False,
)

pred_seg = upsampled_logits.argmax(dim=1)[0]
plt.imshow(pred_seg)

📄 许可证

本项目采用MIT许可证。

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