file = request.files['file'] if file and allowed_file(file.filename): filename = secure_filename(file.filename) file.save(os.path.join(app.config['UPLOAD_FOLDER'], filename)) 什么意思
时间: 2023-12-12 16:05:32 浏览: 40
这是一个 Flask Web 应用程序中的文件上传部分的代码。具体来说,这段代码表示:
1. 从 HTTP 请求中获取名为 "file" 的文件对象。
2. 如果文件对象存在且它的文件名允许上传(通过调用 allowed_file 函数来判断),则执行以下步骤:
- 生成一个安全的文件名(通过调用 secure_filename 函数)。
- 将文件保存到指定的上传文件夹中(通过调用 os.path.join 函数拼接文件路径)。
其中,app.config['UPLOAD_FOLDER'] 是一个 Flask 应用程序配置的上传文件夹路径。该路径需要在应用程序运行前设置。allowed_file 和 secure_filename 是 Flask 提供的辅助函数,用于验证文件类型和生成安全的文件名。
相关问题
# 上传图片 @app.route("/photo/upload", methods=['POST', "GET"]) def uploads(): if request.method == 'POST': # 获取post过来的文件名称,从name=file参数中获取 file = request.files['file'] if file and allowed_file(file.filename): print(file.filename) # secure_filename方法会去掉文件名中的中文 file_name = secure_filename(file.filename) # 保存图片 file.save(os.path.join(app.config['UPLOAD_FOLDER'], file_name)) return "success" else: return "格式错误,请上传jpg格式文件" return render_template('index.html') 修改成并且返回图片地址
@app.route("/photo/upload", methods=['POST', "GET"])
def uploads():
if request.method == 'POST':
# 获取post过来的文件名称,从name=file参数中获取
file = request.files['file']
if file and allowed_file(file.filename):
print(file.filename)
# secure_filename方法会去掉文件名中的中文
file_name = secure_filename(file.filename)
# 保存图片
file_path = os.path.join(app.config['UPLOAD_FOLDER'], file_name)
file.save(file_path)
# 返回图片地址
return jsonify({'code': 200, 'msg': 'success', 'file_path': file_path})
else:
return jsonify({'code': 400, 'msg': '格式错误,请上传jpg格式文件'})
return render_template('index.html')
注意:这里返回的是json格式的数据,包括上传状态、上传信息和图片地址。
coding=UTF-8 from flask import Flask, render_template, request, send_from_directory from werkzeug.utils import secure_filename from iconflow.model.colorizer import ReferenceBasedColorizer from skimage.feature import canny as get_canny_feature from torchvision import transforms from PIL import Image import os import datetime import torchvision import cv2 import numpy as np import torch import einops transform_Normalize = torchvision.transforms.Compose([ transforms.Normalize(0.5, 1.0)]) ALLOWED_EXTENSIONS = set([‘png’, ‘jpg’, ‘jpeg’]) app = Flask(name) train_model = ReferenceBasedColorizer() basepath = os.path.join( os.path.dirname(file), ‘images’) # 当前文件所在路径 def allowed_file(filename): return ‘.’ in filename and filename.rsplit(‘.’, 1)[1] in ALLOWED_EXTENSIONS def load_model(log_path=‘/mnt/4T/lzq/IconFlowPaper/checkpoints/normal_model.pt’): global train_model state = torch.load(log_path) train_model.load_state_dict(state[‘net’]) @app.route(“/”, methods=[“GET”, “POST”]) def hello(): if request.method == ‘GET’: return render_template(‘upload.html’) @app.route(‘/upload’, methods=[“GET”, “POST”]) def upload_lnk(): if request.method == ‘GET’: return render_template(‘upload.html’) if request.method == ‘POST’: try: file = request.files['uploadimg'] except Exception: return None if file and allowed_file(file.filename): format = "%Y-%m-%dT%H:%M:%S" now = datetime.datetime.utcnow().strftime(format) filename = now + '_' + file.filename filename = secure_filename(filename) basepath = os.path.join( os.path.dirname(file), ‘images’) # 当前文件所在路径 # upload_path = os.path.join(basepath,secure_filename(f.filename)) file.save(os.path.join(basepath, filename)) else: filename = None return filename @app.route(‘/download/string:filename’, methods=[‘GET’]) def download(filename): if request.method == “GET”: if os.path.isfile(os.path.join(basepath, filename)): return send_from_directory(basepath, filename, as_attachment=True) pass def get_contour(img): x = np.array(img) canny = 0 for layer in np.rollaxis(x, -1): canny |= get_canny_feature(layer, 0) canny = canny.astype(np.uint8) * 255 kernel = np.array([ [0, 1, 1, 1, 0], [1, 1, 1, 1, 1], [1, 1, 1, 1, 1], [1, 1, 1, 1, 1], [0, 1, 1, 1, 0], ], dtype=np.uint8) canny = cv2.dilate(canny, kernel) # canny = Image.fromarray(canny) return canny @app.route(‘/embedding//’, methods=[“GET”, “POST”]) def icontran(img, reference): global train_model if request.method == ‘POST’: imgPath = os.path.join(basepath, img) referencePath = os.path.join(basepath, reference) img = cv2.imread(imgPath) if img is None or img.size <= 0: return None contour = get_contour(img).astype(np.float32).copy() contour = 255 - contour reference = cv2.imread(referencePath).astype(np.float32) reference = cv2.cvtColor(reference, cv2.COLOR_BGR2RGB) reference = transform_Normalize(torch.from_numpy(reference).permute(2, 0, 1).unsqueeze(0).float()/ 255.0) contour = transform_Normalize(torch.from_numpy(contour).unsqueeze(0).unsqueeze(0).float()/ 255.0) train_model.eval() transfer = train_model(contour, reference) transfer = transfer.squeeze(0) transfer = (transfer + 0.5).clamp(0, 1).mul_(255).permute(1, 2, 0).type(torch.uint8).numpy() transfer = transfer.numpy() cv2.imwrite(imgPath, transfer) return basepath # success if name == “main”: load_model() app.run(host=‘10.21.16.144’, port=9999, debug=True) 用puthon写一个调用这个服务器的gui
这是一段 Python 代码,它使用 Flask 框架来创建一个网站应用。它还导入了一些需要使用的库,如 werkzeug、numpy、torch 等。该代码可以对图片进行一些处理,如调整亮度、色彩等。其中包括一个可以将黑白图片变成彩色图片的算法 train_model。同时,代码中使用了一些图像处理的函数和变换,如 canny 算法和 einops。最后,它可以将处理后的图片保存在指定的文件夹中,并在网页中展示出来。