Clip Vit Large Patch14 Plant Disease Finetuned

🚀 clip-vit-large-patch14-finetuned-disease

本模型是 openai/clip-vit-large-patch14 在自定义数据集上针对植物病害描述进行微调后的版本。它旨在对植物叶片图像进行分类，并生成描述叶片病害或健康状况的说明。

✨ 主要特性

• 基于 openai/clip-vit-large-patch14 模型进行微调，适用于植物病害分类和描述生成。
• 利用 CLIP 架构将叶片图像映射到描述性说明，辅助植物病害的诊断和分类。

📦 安装指南

文档未提供安装步骤，暂不展示。

💻 使用示例

基础用法

from transformers import CLIPProcessor, CLIPModel
from PIL import Image
import requests

# Load the model and processor
model = CLIPModel.from_pretrained("Keetawan/clip-vit-large-patch14-plant-disease-finetuned")
processor = CLIPProcessor.from_pretrained("Keetawan/clip-vit-large-patch14-plant-disease-finetuned")

# Load an image of a plant leaf
image_url = "https://example.com/path_to_your_image.jpg"
image = Image.open(requests.get(image_url, stream=True).raw)

# Prepare the image
inputs = processor(text=["Apple leaf with Apple scab", "Healthy Tomato leaf", ...], images=image, return_tensors="pt", padding=True)

# Get predictions
outputs = model(**inputs)
logits_per_image = outputs.logits_per_image  # Image-text similarity score
probs = logits_per_image.softmax(dim=1)  # Convert logits to probabilities

# Print the most likely label
predicted_label = probs.argmax().item()
labels = [
    "Apple leaf with Apple scab",
    "Apple leaf with Black rot",
    ...
    "Healthy Tomato leaf"
]
print(f"Predicted label: {labels[predicted_label]}")

📚 详细文档

模型描述

clip-vit-large-patch14-finetuned-disease 模型在专门为识别影响植物叶片的各种病害而策划的数据集上进行了微调。该模型使用 CLIP 架构将叶片图像映射到描述性说明，有助于植物病害的诊断和分类。

标签和描述

该模型经过训练，可对以下植物病害和状况进行分类：

{
  0: "带有苹果黑星病的苹果叶",
  1: "带有黑腐病的苹果叶",
  2: "带有雪松苹果锈病的苹果叶",
  3: "健康的苹果叶",
  4: "带有尾孢菌叶斑病（灰斑病）的玉米叶",
  5: "带有普通锈病的玉米叶",
  6: "带有北方叶枯病的玉米叶",
  7: "健康的玉米叶",
  8: "带有藻斑病的榴莲叶",
  9: "带有叶枯病的榴莲叶",
  10: "带有叶斑病的榴莲叶",
  11: "健康的榴莲叶",
  12: "带有黑腐病的葡萄叶",
  13: "带有埃斯卡病（黑麻疹病）的葡萄叶",
  14: "带有叶枯病（伊萨里叶斑病）的葡萄叶",
  15: "健康的葡萄叶",
  16: "带有褐色斑点的油棕叶",
  17: "健康的油棕叶",
  18: "带有白蚧的油棕叶",
  19: "带有黄龙病（柑橘绿化病）的橙子叶",
  20: "带有细菌性斑点病的甜椒叶",
  21: "健康的甜椒叶",
  22: "带有早疫病的马铃薯叶",
  23: "带有晚疫病的马铃薯叶",
  24: "健康的马铃薯叶",
  25: "带有细菌性叶枯病的水稻叶",
  26: "带有稻瘟病的水稻叶",
  27: "带有褐斑病的水稻叶",
  28: "带有东格鲁病的水稻叶",
  29: "健康的大豆叶",
  30: "带有叶焦病的草莓叶",
  31: "健康的草莓叶",
  32: "带有细菌性斑点病的番茄叶",
  33: "带有早疫病的番茄叶",
  34: "带有晚疫病的番茄叶",
  35: "带有叶霉病的番茄叶",
  36: "带有 Septoria 叶斑病的番茄叶",
  37: "带有红蜘蛛（二斑叶螨）的番茄叶",
  38: "带有靶斑病的番茄叶",
  39: "带有番茄黄叶曲叶病毒病的番茄叶",
  40: "带有番茄花叶病毒病的番茄叶",
  41: "健康的番茄叶"
}

📄 许可证

文档未提供许可证信息，暂不展示。

📚 引用

如果您在研究或应用中使用此模型，请按以下方式引用：

@misc{keetawan2024plantdisease,
  author = {Keetawan Limaroon},
  title = {clip-vit-large-patch14-finetuned-disease: A fine-tuned model for plant disease classification and captioning},
  year = {2024},
  publisher = {Hugging Face},
  url = {https://huggingface.co/Keetawan/clip-vit-large-patch14-plant-disease-finetuned},
}