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http - 如何解码从服务器发送到 Flutter 应用程序的图像？

问题描述

我正在将我的 json 响应从服务发送到我的 Flutter 应用程序。API 处理从移动设备获取图像到服务器并检测对象。检测后，从服务器发送的响应正文是一个图像，该图像具有对图像中检测到的类的注释。我正在向它发送一个在 toString() 的帮助下编码的编码图像文件。服务器端代码：

import time
from absl import app, logging
import cv2
import numpy as np
import tensorflow as tf
from yolov3_tf2.models import (
    YoloV3, YoloV3Tiny
)
from yolov3_tf2.dataset import transform_images, load_tfrecord_dataset
from yolov3_tf2.utils import draw_outputs
from flask import Flask, request, Response, jsonify, send_from_directory, abort
import os

# customize your API through the following parameters
classes_path = './data/labels/obj.names'
weights_path = './weights/yolov3-tiny.tf'
tiny = True                    # set to True if using a Yolov3 Tiny model
size = 416                      # size images are resized to for model
output_path = './detections/'   # path to output folder where images with detections are saved
num_classes = 1               # number of classes in model

# load in weights and classes
physical_devices = tf.config.experimental.list_physical_devices('GPU')
if len(physical_devices) > 0:
    tf.config.experimental.set_memory_growth(physical_devices[0], True)

if tiny:
    yolo = YoloV3Tiny(classes=num_classes)
else:
    yolo = YoloV3(classes=num_classes)

yolo.load_weights(weights_path).expect_partial()
print('weights loaded')

class_names = [c.strip() for c in open(classes_path).readlines()]
print('classes loaded')

# Initialize Flask application
app = Flask(_name_)

# API that returns image with detections on it
@app.route('/image', methods= ['POST'])
def get_image():
    image = request.files["images"]
    image_name = image.filename
    image.save(os.path.join(os.getcwd(), image_name))
    img_raw = tf.image.decode_image(
        open(image_name, 'rb').read(), channels=3)
    img = tf.expand_dims(img_raw, 0)
    img = transform_images(img, size)

    t1 = time.time()
    boxes, scores, classes, nums = yolo(img)
    t2 = time.time()
    print('time: {}'.format(t2 - t1))

    print('detections:')
    for i in range(nums[0]):
        print('\t{}, {}, {}'.format(class_names[int(classes[0][i])],
                                        np.array(scores[0][i]),
                                        np.array(boxes[0][i])))
    img = cv2.cvtColor(img_raw.numpy(), cv2.COLOR_RGB2BGR)
    img = draw_outputs(img, (boxes, scores, classes, nums), class_names)
    cv2.imwrite(output_path + 'detection.jpg', img)
    print('output saved to: {}'.format(output_path + 'detection.jpg'))

    # prepare image for response
    _, img_encoded = cv2.imencode('.jpg', img)
    response = img_encoded.tostring()
    #remove temporary image
    os.remove(image_name)

    try:
        return Response(response=response, status=200, mimetype='image/jpg') 
    except FileNotFoundError:
        abort(404)
if _name_ == '_main_':
    app.run(debug=True, host = '0.0.0.0', port=5000)

客户端代码

final String url_API = "http://18b8b114.ngrok.io/image";                       //Post the image to the Object detection API for classification                                               Future <Response> dio_upload(String imagePath) async {  

      http.MultipartRequest request = http.MultipartRequest('POST', Uri.parse(url_API));
      request.files.add(
      await http.MultipartFile.fromPath(
      'images',
      image.path,
      contentType: MediaType('application', 'jpeg'),
    ),
  );

  http.StreamedResponse response = await request.send();
  print(response.statusCode);
  print(await response.stream.transform(utf8.decoder).join());

最后一个打印语句引发错误，指出错误的 UTF 字符串。我应该以什么形式解码响应？这是我唯一知道的 MultipartRequest 代码。

标签： httpflutterdart

解决方案

好吧，创建一个 static_url_path 并访问图像将很容易完成这项工作。

 app = Flask(__name__, static_url_path='/static')

此外，创建从目录发送的路由也可以完美运行。

@app.route('/result')
def send_js():
    return send_from_directory('static/images', 'detection.jpg')

然后简单地在颤振中使用 NetworkImage 可以帮助获取图像:)

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