def check_equipment(self, template_path):
"""
查找装备
:param template_path: 模板目录
:return: {'r': 相似度, 'x': x坐标, 'y': y坐标， 'path': 模板路径}
"""
THRESHOLD = 0.55
found = None
return_list = list()
screen = self.d.screenshot(format="opencv")
# 遍历所有的图片寻找模板
for imagePath in glob.glob(template_path + "/*"):
self.log.debug("> " + imagePath)
# result = UIMatcher.multi_scale_template_match(screen, imagePath)
w, h = screen.shape[:2]
item_w = w / 10
scale = 128 / item_w # TODO：128为模板宽，应修改为自动检测
result = UIMatcher.multi_scale_template_match(screen,
imagePath,
min_scale=scale,
max_scale=scale,
step=1)
if result['r'] > THRESHOLD:
result['path'] = imagePath
return_list.append(result)
# 切割物品图标
ocr.divide(return_list, screen)
# 切割物品数量, 识别数字
ocr.ocr(return_list)
return return_list
def server():
if request.method == 'POST' or request.method == 'GET':
if request.files.__len__() == 0:
flash('No file part')
return redirect(request.url)
file = request.files['image']
if file.filename == '':
flash('No selected file')
return redirect(request.url)
if file and allowed_file(file.filename):
filename = secure_filename(file.filename)
path = os.path.join(app.config['UPLOAD_FOLDER'], filename)
file.save(path)
copyPath = os.path.join('../../www/upload', filename)
print file.filename, path, copyPath
copyfile(path, copyPath)
if file.filename == 'receipt1.jpg':
return json.dumps(preset1)
elif file.filename == 'receipt2.jpg':
return json.dumps(preset2)
elif file.filename == 'receipt3.jpg':
return json.dumps(preset3)
elif file.filename == 'receipt4.jpg':
return json.dumps(preset4)
else:
response = ocr(
path,
os.path.join(
'http://52.12.74.177/upload',
filename,
),
)
return response
return 'error'
def test4pointTransformBBP(self):
return
test_img = [('testcase/4pOCR/577.png', '577'),
('testcase/4pOCR/04162.png', '04162')]
for (fname, realText) in test_img:
img = cv2.imread(path + '/' + fname)
org = img.copy()
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
contour = cv2.findContours(img, cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)[1]
text = ''
for c in contour:
(x, y, w, h) = cv2.boundingRect(c)
if (w * h) < 50:
continue
cropImg = img[y:y + h, x:x + w]
c0 = cv2.findContours(cropImg, cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)[1][0]
if (len(c0) == 0):
continue
rect = cv2.minAreaRect(c0)
box = np.int0(cv2.boxPoints(rect))
newImg = four_point_transform(cropImg, box)
text = text + ocr.ocr(newImg, method='bbp')
print('{} - BBP return {}, real is {}'.format(
fname, text, realText))
self.assertTrue(True)
def read(path: str):
"""
`path` to image file
"""
image = cv2.imread(path)
# cv2.imshow("original", image)
# cv2.waitKey(0)
image = preprocess(image)
# cv2.imshow("processed", image)
# cv2.waitKey(0)
text = ocr(image)
# print(text)
receipt = parse(text)
return receipt