我有一个Python-Flask应用程序，在该应用程序中，我将图像上传到服务器，并使用this tutorial之后的密集网模型对选定的上传图像执行预测，这会导致以下错误：PIL.UnidentifiedImageError: cannot identify image file <_io.BytesIO object at 0x7f4ceb257950>
以下是我的预测路线：

@app.route('/predict', methods=['POST'])
@login_required
def predict():
    if request.method == 'POST':

        filename = ""
        if len(request.form) == 0:
            flash("Please select a file to perform a prediction on")
            return redirect(url_for('index'))
        else:

            filename = request.form['file']
            filepath = os.path.join(app.config['UPLOAD_PATH'], \
                                     current_user.username, filename)
            
            file = open(filepath, 'rb')
            img_bytes = file.read()
            class_id, class_name = models.get_prediction(image_bytes=img_bytes)
            print(class_id, class_name)

    return render_template('predict.html', filename=filename)

models.py:

import io
import json
import os

from torchvision import models
import torchvision.transforms as transforms
from PIL import Image

imagenet_class_index = json.load(open('imagenet_class_index.json'))
model = models.densenet121(pretrained=True)
model.eval()

def transform_image(image_bytes):
    my_transforms = transforms.Compose([transforms.Resize(255),
                                        transforms.CenterCrop(224),
                                        transforms.ToTensor(),
                                        transforms.Normalize(
                                            [0.485, 0.456, 0.406],
                                            [0.229, 0.224, 0.225])])
    
    image = Image.open(io.BytesIO(image_bytes))
    return my_transforms(image).unsqueeze(0)

def get_prediction(image_bytes):
    tensor = transform_image(image_bytes=image_bytes)
    outputs = model.forward(tensor)
    _, y_hat = outputs.max(1)
    predicted_idx = str(y_hat.item())
    return imagenet_class_index[predicted_idx]

堆栈跟踪：

[2023-03-03 13:49:32,564] ERROR in app: Exception on /predict [POST]
Traceback (most recent call last):
  File "/mnt/c/Users/sahan/Desktop/Senior Year/CS 81a/Sahana-cs81a/venv/lib/python3.8/site-packages/flask/app.py", line 2525, in wsgi_app
    response = self.full_dispatch_request()
  File "/mnt/c/Users/sahan/Desktop/Senior Year/CS 81a/Sahana-cs81a/venv/lib/python3.8/site-packages/flask/app.py", line 1822, in full_dispatch_request        
    rv = self.handle_user_exception(e)
  File "/mnt/c/Users/sahan/Desktop/Senior Year/CS 81a/Sahana-cs81a/venv/lib/python3.8/site-packages/flask/app.py", line 1820, in full_dispatch_request        
    rv = self.dispatch_request()
  File "/mnt/c/Users/sahan/Desktop/Senior Year/CS 81a/Sahana-cs81a/venv/lib/python3.8/site-packages/flask/app.py", line 1796, in dispatch_request
    return self.ensure_sync(self.view_functions[rule.endpoint])(**view_args)
  File "/mnt/c/Users/sahan/Desktop/Senior Year/CS 81a/Sahana-cs81a/venv/lib/python3.8/site-packages/flask_login/utils.py", line 290, in decorated_view        
    return current_app.ensure_sync(func)(*args, **kwargs)
  File "/mnt/c/Users/sahan/Desktop/Senior Year/CS 81a/Sahana-cs81a/cloudsystem/app.py", line 311, in predict
    class_id, class_name = models.get_prediction(image_bytes=img_bytes)
  File "/mnt/c/Users/sahan/Desktop/Senior Year/CS 81a/Sahana-cs81a/cloudsystem/models.py", line 25, in get_prediction
    tensor = transform_image(image_bytes=image_bytes)
  File "/mnt/c/Users/sahan/Desktop/Senior Year/CS 81a/Sahana-cs81a/cloudsystem/models.py", line 21, in transform_image
    image = Image.open(io.BytesIO(image_bytes))
  File "/mnt/c/Users/sahan/Desktop/Senior Year/CS 81a/Sahana-cs81a/venv/lib/python3.8/site-packages/PIL/Image.py", line 3283, in open
    raise UnidentifiedImageError(msg)
PIL.UnidentifiedImageError: cannot identify image file <_io.BytesIO object at 0x7f4c48b2ea40>

我已经尝试了this没有成功，以及确保只有有效的文件类型（即.png，.jpg）可以上传。我也尝试过传入路径名而不是文件字节，这将导致FileNotFoundError。我已经仔细检查了路径是否正确，并且该文件确实存在于我的本地目录中。使用OpenCV将导致与上面相同的错误。目前，我只希望预测结果能在终端打印出来，谢谢！
Edit（1）：以下是传入PIL的image_bytes的前20个字节：“五...四...”
Edit（2）：由于文件的字节数与任何图像格式都不对应，我尝试将图像路径传入Image.open()：

if os.path.isfile(filepath):
        print(filepath + " is a valid file from app.py")
class_id, class_name = models.get_prediction(filepath)

print语句打印路径，所以我假设传入models.get_prediction()的路径是有效的。
transform_image()函数现在如下所示：

def transform_image(path):
    my_transforms = transforms.Compose([transforms.Resize(255),
                                        transforms.CenterCrop(224),
                                        transforms.ToTensor(),
                                        transforms.Normalize(
                                            [0.485, 0.456, 0.406],
                                            [0.229, 0.224, 0.225])])
    
    if os.path.isfile(path):
        print(path + " is a valid file from models.py")    
    image = Image.open(path)
    return my_transforms(image).unsqueeze(0)

同样，输入文件的路径正在打印，所以文件必须存在于路径中。但是，我仍然从Image.open(path)得到以下错误：PIL.UnidentifiedImageError: cannot identify image file 'uploads/test/Cat03.jpg .