我有一個 Image 物件,需要傳遞給客戶端并顯示在頁面上。以下是我嘗試過但無濟于事的方法。
model_predict 函式正在從客戶端接收影像以進行分類。分類完成后,模型將生成一張影像,并在函式 upload() 中傳回客戶端。
def model_predict(img_path, model):
img = image.load_img(img_path, target_size=(224, 224))
...
leaf_result = cv2.bitwise_and(img, img, mask=mask)
im = Image.fromarray(leaf_result)
# decoded_class = decode(img)
im.save(f"./output.png")
preds = model.predict(x)
return preds,im
@app.route('/predict', methods=['GET', 'POST'])
def upload():
if request.method == 'POST':
# Get the file from post request
f = request.files['file']
# Save the file to ./uploads
basepath = os.path.dirname(__file__)
file_path = os.path.join(
basepath, 'uploads', secure_filename(f.filename))
f.save(file_path)
prediction, im = model_predict(file_path, model)
....
result_list = list()
result_list.append(prediction1)
result_list.append(prediction2)
return jsonify(result_list, base64.decodebytes(im))
return None
uj5u.com熱心網友回復:
Base64 編碼是您所需要的:將 base64 資料發送到客戶端,然后您的客戶端將對其進行解碼。燒瓶回傳影像
例如:
import io
import base64
# import flask
from PIL import Image
def get_encoded_img(image_path):
img = Image.open(image_path, mode='r')
img_byte_arr = io.BytesIO()
img.save(img_byte_arr, format='PNG')
my_encoded_img = base64.encodebytes(img_byte_arr.getvalue()).decode('ascii')
return my_encoded_img
...
# your api code
...
img_path = 'assets/test.png'
img = get_encoded_img(img_path)
# prepare the response: data
response_data = {"key1": value1, "key2": value2, "image": img}
# return flask.jsonify(response_data )
當您的客戶端收到 base64 資料時,它可以使用 naive JS 顯示該影像。如何在 HTML 中顯示 Base64 影像
例如:
<img id="image"/>
<script>
var ticket = {
"validationDataValidDate": "2019-05-30",
"validationImage": "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 fkUd/fvz8 fPuX3/lTJ48ebK2tmmyxr8lWbsTHcOB/yAaayG5J n49yR776FkV8kku/w3IiD/A4V hQQgINlNcWTDZIdKFtvAeig6WGdIvgX2rZ52iTu5j3RJsuEz4bqZCvclJwygEI4UCCbZ3c3GTkexA/W4NIYNuiSp6ncP/yzpJRaS7f2eZJeYy/ehZEDMIILyAEh6pokhSTe/xSGZI5gD Xt/S6 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