From 2f97072a550d21f4375c04baa31348d9b3938c43 Mon Sep 17 00:00:00 2001
From: UnknownObject <me@unsmail.ltd>
Date: Wed, 6 Dec 2023 15:31:04 +0800
Subject: [PATCH] =?UTF-8?q?=E4=BF=AE=E5=A4=8D=E4=BA=86=E6=9B=B4=E8=AF=A1?=
 =?UTF-8?q?=E5=BC=82=E7=9A=84BUG=E3=80=82?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 ver3.py | 64 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 64 insertions(+)
 create mode 100644 ver3.py

diff --git a/ver3.py b/ver3.py
new file mode 100644
index 0000000..aa284c0
--- /dev/null
+++ b/ver3.py
@@ -0,0 +1,64 @@
+from fastai.data.transforms import get_image_files, parent_label, RandomSplitter, Normalize
+from fastai.learner import load_learner
+from fastai.metrics import error_rate
+from pathlib import Path
+from fastai.data.block import CategoryBlock, DataBlock
+from fastai.vision.all import *
+from fastai.vision.augment import Resize, aug_transforms
+from fastai.vision.core import imagenet_stats
+from fastai.vision.data import ImageBlock
+from fastai.vision.learner import cnn_learner, vision_learner
+from torchvision.models import resnet34
+from PIL import Image
+
+
+def open_image(image_path):
+    img = Image.open(image_path)
+    img_cvt = img.resize((460,460))
+    return img
+
+
+def predict_image(image_path):
+    # 加载模型
+    model = load_learner('G:\\Users\\15819\\Desktop\\model01.pkl')
+    # 读取图片并转换为Tensor
+    img = open_image(image_path)  # 读取指定路径（image_path）下的图像文件
+    # 进行预测
+    pred_class, pred_idx, outputs = model.predict(img)
+    # 获取置信度
+    # 检查输出张量的维度
+    if outputs.dim() == 0:
+        confidence = float(outputs)
+    else:
+        confidence = float(outputs[pred_idx])
+
+    return pred_class, confidence
+
+def train():
+    data_path = Path('G:\\Users\\15819\\Desktop\\Images2')
+    export_path = Path('G:\\Users\\15819\\Desktop')
+    blocks = (ImageBlock, CategoryBlock)
+    batch_size = 32
+    dls = DataBlock(
+        blocks=blocks,
+        get_items=get_image_files,
+        splitter=RandomSplitter(),
+        get_y=parent_label,
+        item_tfms=Resize(460),
+        batch_tfms=[*aug_transforms(size=224, min_scale=0.75), Normalize.from_stats(*imagenet_stats)]
+    ).dataloaders(data_path, num_workers=4, bs=batch_size)
+
+    model = vision_learner(dls, resnet34, metrics=error_rate)
+    model.fine_tune(5, freeze_epochs=3)
+    model.export('G:\\Users\\15819\\Desktop\\model01.pkl')
+
+def main():
+    #train()
+
+    image_path = 'G:\\Users\\15819\\Desktop\\Images2\\SmallCar\\京M88888.jpg'
+    pred_class, confidence = predict_image(image_path)
+    print(f"图片类别： {pred_class}, 置信度： {confidence}")
+
+
+if __name__ == '__main__':
+    main()