Question

我正在尝试使用Flask包装器将图像上传到TF-Inception模型，但这是我在通过邮递员测试时遇到的错误。我已经尝试了很多谷歌搜索/但没有找到一种方法来弄清楚如何解决最初的image_data部分

image_data = tf.gfile.FastGFile(image_path, 'rb').read()

但是我已经改变它以使用烧瓶的请求模块接受图像数据，并且这一直是空的

image_data = request.data

但我想传递我正在上传的图片文件的数据。

错误：

InvalidArgumentError (see above for traceback): Invalid JPEG data, size 0
     [[Node: DecodeJpeg = DecodeJpeg[acceptable_fraction=1, channels=3, dct_method="", fancy_upscaling=true, ratio=1, try_recover_truncated=false, _device="/job:localhost/replica:0/task:0/cpu:0"](_recv_DecodeJpeg/contents_0)]]

代码：

from flask import Flask, request
import tensorflow as tf
import sys

app = Flask(__name__)

@app.route("/classify", methods=["POST"])
def classify():
    image_data = request.data
    #loads label file, strips off carriage return
    label_lines = [line.strip() for line in tf.gfile.GFile("/tmp/output_labels.txt")]

    # Unpersists graph from file
    with tf.gfile.FastGFile("/tmp/output_graph.pb", 'rb') as f:
        graph_def = tf.GraphDef()
        graph_def.ParseFromString(f.read())
        _ = tf.import_graph_def(graph_def, name='')

    with tf.Session() as sess:
        # Feed the image data as input to the graph an get first prediction
        softmax_tensor = sess.graph.get_tensor_by_name('final_result:0')
        predictions = sess.run(softmax_tensor, \
             {'DecodeJpeg/contents:0':image_data})
        # Sort to show labels of first prediction in order of confidence
        top_k = predictions[0].argsort()[-len(predictions[0]):][::-1]

        for node_id in top_k:
            human_string = label_lines[node_id]
            score = predictions[0][node_id]
            print('%s (score = %.2f)' % (human_string, score))

if __name__ == '__main__':
    app.run()

Answer 1

（完全重写答案，谢谢澄清）

所以，据我所知，你的代码在直接使用文件名时效果很好，但是一旦你尝试从 POST 中读取文件就失败了。

在您的代码中，您可以像这样检索文件：

image_data = request.data

Looking around the web我发现你应该得到这样的数据：

# check if the post request has the file part
if 'file' not in request.files:
    flash('No file part')
    return redirect(request.url)
file = request.files['file']

Tensorflow初始图像上传

1 个答案: