def aaa(request):
if request.method == 'GET':
return render(request, 'aaa.html')
file = request.FILES.get('file')
b = b''
for c in file.chunks():
b += c
try:
ocr = CnOcr()
except:
pass
sep = ','
img_data = plt.imread(BytesIO(b), "png")
# print(type(img_data))
# print(img_data.shape)
image = img_data[:, :, :3]
# print(image.shape)
image = (image * 255).astype(np.int)
try:
res = ocr.ocr_for_single_line(image)
msg = sep.join(res).replace(',', '')
data = {'code': 200, 'msg': msg}
return JsonResponse(data)
except:
msg = '图片名含有非转义字符，建议使用数字字母的形式'
data = {'code': 400, 'msg': msg}
return JsonResponse(data)
def get_list(self):
std=CnStd()
ocr=CnOcr()
ocr._model_name='conv-lite-fc'
print(ocr._model_name)
ocr_res2=ocr.ocr(img_fp=self.filepath)
box_info_list=std.detect(self.filepath,pse_threshold=0.7,pse_min_area=150,context='gpu',height_border=0.10)
image=Image.open(self.filepath)
fontstyle=ImageFont.truetype('./simhei.ttf',13,encoding='utf-8')
draw=ImageDraw.Draw(image)
for box_info in box_info_list:
print('a')
print('a')
print(box_info)
info_box=box_info['box']
crp_img=box_info['cropped_img']
ocr_res1=ocr.ocr_for_single_line(crp_img)
print('result: %s' % ''.join(str(ocr_res1)))
x1,y1=info_box[0,0],info_box[0,1]
x2,y2=info_box[1,0],info_box[1,1]
x3,y3=info_box[2,0],info_box[2,1]
x4,y4=info_box[3,0],info_box[3,1]
draw.polygon([(x1,y1),(x4,y4),(x3,y3),(x2,y2)],outline=(255,0,0))
draw.text((x4,y4),str(ocr_res1),(200,0,0),font=fontstyle)
image.show()
print(ocr_res2)
return box_info_list
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--model_name",
help="model name",
type=str,
default='conv-lite-fc')
parser.add_argument("--model_epoch",
type=int,
default=None,
help="model epoch")
parser.add_argument("-f", "--file", help="Path to the image file")
parser.add_argument(
"-s",
"--single-line",
default=False,
help="Whether the image only includes one-line characters",
)
args = parser.parse_args()
ocr = CnOcr(model_name=args.model_name, model_epoch=args.model_epoch)
if args.single_line:
res = ocr.ocr_for_single_line(args.file)
else:
res = ocr.ocr(args.file)
logger.info("Predicted Chars: %s", res)
def main():
parser = argparse.ArgumentParser()
parser.add_argument("-f", "--file", help="Path to the CAPTCHA image file")
args = parser.parse_args()
ocr = CnOcr()
res = ocr.ocr_for_single_line(args.file)
print("Predicted Chars:", res)
async def Img2Text(img: Image, ocr_model: CnOcr, std: CnStd) -> str:
url = img.url
async with aiohttp.ClientSession() as session:
async with session.get(url=url) as resp:
img_content = await resp.read()
img = IMG.open(BytesIO(img_content)).convert("RGB")
img = numpy.array(img)
box_info_list = std.detect(img)
res = []
for box_info in box_info_list:
cropped_img = box_info['cropped_img'] # 检测出的文本框
ocr_res = ocr_model.ocr_for_single_line(cropped_img)
res.append([ocr_res])
print(res)
return "".join(await flat(res))
def main():
parser = argparse.ArgumentParser()
parser.add_argument("-f", "--file", help="Path to the image file")
parser.add_argument(
"-s",
"--single-line",
default=False,
help="Whether the image only includes one-line characters")
args = parser.parse_args()
ocr = CnOcr()
if args.single_line:
res = ocr.ocr_for_single_line(args.file)
else:
res = ocr.ocr(args.file)
print("Predicted Chars:", res)
def orc_text(path_image):
ocr = CnOcr()
image = cv2.imread(path_image, cv2.IMREAD_GRAYSCALE)
height_image, width_image = image.shape
_, binary_image = cv2.threshold(image, 150, 255, cv2.THRESH_BINARY_INV)
height_projection = get_horizontal_projection(binary_image)
text_lines = get_text_lines(height_projection)
text_list = []
for line_index, text_line in enumerate(text_lines):
text_line_image = binary_image[text_line[0]:text_line[1],
0:width_image]
vertical_projection = get_vertical_projection(text_line_image)
text_words = get_text_word(vertical_projection)
text_line_word_image = image[text_line[0]:text_line[1],
text_words[0][0]:text_words[-1][1]]
res = ocr.ocr_for_single_line(text_line_word_image)
text_list.append(''.join(res))
return text_list
def extract_content(save_dir_path):
std = CnStd()
cn_ocr = CnOcr()
base_path = os.path.abspath(os.path.dirname(__file__))
pic_base_dir = os.path.join(base_path, "received")
pic_path_list = (glob.glob(os.path.join(pic_base_dir, "*.png")) +
glob.glob(os.path.join(pic_base_dir, "*.jpg")) +
glob.glob(os.path.join(pic_base_dir, "*.jpeg")))
workbook = xlwt.Workbook()
for index, pic_path in enumerate(pic_path_list):
sheet = workbook.add_sheet('sheet{}'.format(index),
cell_overwrite_ok=True)
box_info_list = std.detect(pic_path)
for box_info in box_info_list:
x_list, y_list = [], []
for (x, y) in box_info['box']:
x_list.append(x)
y_list.append(y)
top, bottom, left, right = min(y_list), max(y_list), min(
x_list), max(x_list)
top_row, bottom_row, left_column, right_column = int(
top // 80), int(bottom // 80), int(left // 60), int(right //
60)
cropped_img = box_info['cropped_img'] # 检测出的文本框
ocr_res = ''.join(cn_ocr.ocr_for_single_line(cropped_img))
try:
logger.info(
"top_row:{}, bottom_row:{}, left_column:{}, right_column:{}, ocr_res:{}",
top_row,
bottom_row,
left_column,
right_column,
ocr_res,
feature="f-strings")
sheet.write_merge(top_row, bottom_row, left_column,
right_column, ocr_res)
except Exception as e:
print(e)
xls_base_dir = os.path.join(base_path, save_dir_path)
xls_path = os.path.join(xls_base_dir, "res.xls")
workbook.save(xls_path)
def ocr():
if 'file' not in request.files:
return jsonify(code=-1, message='no file error'), 400
file = request.files['file']
_uuid = str(uuid.uuid1())
file_name = '/tmp/ocr/' + _uuid
file.save(file_name)
ocr = CnOcr(name=_uuid)
std = CnStd(name=_uuid)
box_info_list = std.detect(file_name)
lines = []
for box_info in box_info_list:
cropped_img = box_info['cropped_img'] # 检测出的文本框
ocr_res = ocr.ocr_for_single_line(cropped_img)
lines.append(''.join(ocr_res))
return jsonify(code=0, message='ok', data=lines)
def to_raw_srt(path, srt_dir):
ocr = CnOcr()
if not os.path.exists(srt_dir):
os.mkdir(srt_dir)
dir_list = [int(r) for r in os.listdir(path) if r.isdigit()]
dir_list.sort()
file = srt_dir + '/to_srt' + '.txt'
if os.path.exists(file):
os.remove(file)
for i in dir_list:
child_dir = path + '/' + str(i)
file_list = os.listdir(child_dir)
for j in file_list:
frame_no = str(child_dir.split('/')[-1])
text_position = j.split('.')[0]
# OCR识别调用
content = cleantxt("".join(ocr.ocr_for_single_line(child_dir + '/' + j)))
with open(file, 'a+') as f:
f.write(frame_no + '\t' + text_position + '\t' + content + '\r\n')
f.close()
def target_function(idx, ls, prefix):
# 使得每一张卡都能被充分用到
# 提交的时候由于只有一张卡，需要全部都改成0
os.environ['CUDA_VISIBLE_DEVICES'] = '0'
std = CnStd(context='gpu')
cn_ocr = CnOcr(context='gpu')
result = dict()
for file_name in tqdm(ls):
file_path = os.path.join(prefix, file_name)
box_info_list = std.detect(file_path)
output = ''
for box_info in box_info_list:
cropped_img = box_info['cropped_img'] # 检测出的文本框
if type(cropped_img) != type(None):
ocr_res = cn_ocr.ocr_for_single_line(cropped_img)
output += ''.join(ocr_res)
# print('ocr result: %s' % ''.join(ocr_res))
output = output.replace(' ', '')
output = re.sub("[^\u4e00-\u9fa5]", "", output)
result[file_name] = output
with open('./output_%d.json' % (idx), 'w', encoding='utf-8') as w:
w.write(json.dumps(result, ensure_ascii=False, indent=2))
from cnocr import CnOcr
import cnocr
from cnstd import CnStd
std=CnStd()
ocr=CnOcr()
box_info_list=std.detect('E:\\Work Place\\pocr\\pic\\2.png')
res=ocr.ocr('E:\\Work Place\\pocr\\pic\\1.png')
for box_info in box_info_list:
crp_img=box_info['cropped_img']
ocr_res=ocr.ocr_for_single_line(crp_img)
print('result: %s' % ''.join(ocr_res))
class GUIMainWin(QMainWindow, Ui_ArknightsRecruimentHelperGUI):
def __init__(self, parent=None):
super(GUIMainWin, self).__init__(parent)
# Basic Setups
self.setupUi(self)
self.appExceptionHandler = ExceptHookHandler(
self,
logFile=os.path.join(os.path.expanduser('~'),
"ArknightsRecruitmentHelper", "log.txt"))
self.setWindowTitle(globalVersion)
# Key Initializations
self.handle = 0
self.initializeHandleSelector()
self.tagImageSceneList = [
QGraphicsScene(),
QGraphicsScene(),
QGraphicsScene(),
QGraphicsScene(),
QGraphicsScene()
]
self.tagTypeList = ["", "", "", "", ""]
# Handler Connections
self.handleSelectorComboBox.activated[str].connect(self.onHandleSelect)
self.updateHandleSelectorListButton.clicked.connect(
self.initializeHandleSelector)
self.manualRecognizeAndAnalyzeButton.clicked.connect(
self.recognizeAndAnalyze)
self.updateDataButton.clicked.connect(self.updateData)
self.ocrInstance = CnOcr(model_name='conv-lite-fc')
def initializeHandleSelector(self):
emulator_lst = dict()
emulator_hwnd = ["subWin", "canvasWin", "BlueStacksApp"
] # subWin: nox, ldplayer | canvasWin: mumu
def check_emulator_window(hwnd, p):
if win32gui.GetClassName(
hwnd) in emulator_hwnd and hwnd not in emulator_lst:
emulator_lst.update({hwnd: p})
else:
win32gui.EnumChildWindows(hwnd, check_emulator_window, p)
def gui_get_all_hwnd(hwnd, mouse):
if win32gui.IsWindow(hwnd) and win32gui.IsWindowEnabled(
hwnd) and win32gui.IsWindowVisible(hwnd):
if win32gui.GetClassName(
hwnd) == "UnityWndClass" and win32gui.GetWindowText(
hwnd
) == "PrincessConnectReDive": # DMM Game Player
# emulator_lst.update({hwnd: "DMM_PrincessConnectReDive"})
print("yo!")
else:
win32gui.EnumChildWindows(hwnd, check_emulator_window,
win32gui.GetWindowText(hwnd))
win32gui.EnumWindows(gui_get_all_hwnd, 0)
self.handleList = []
for h, t in emulator_lst.items():
if t is not "":
self.handleList.append([h, t])
self.titleList = [handle[1] for handle in self.handleList]
self.handleSelectorComboBox.clear()
self.handleSelectorComboBox.addItems(self.titleList)
if len(self.titleList) == 1:
self.handle = list(emulator_lst.keys())[0]
self.queryStatusTag.setText('等待查询')
self.queryStatusTag.setStyleSheet("color:green")
else:
self.queryStatusTag.setText("请选择句柄")
self.queryStatusTag.setStyleSheet("color:red")
def onHandleSelect(self, handleTitle):
def getHandle(handleTitle):
for handle in self.handleList:
if handle[1] == handleTitle:
return handle
targetHandle = getHandle(handleTitle)
self.handle = targetHandle[0]
self.queryStatusTag.setText("等待查询")
self.queryStatusTag.setStyleSheet("color:green")
def recognizeAndAnalyze(self, slotNum: [0, 1, 2, 3]):
strategyListDict = util.config_loadStrategyListDict()
self.tagOneLabel.setText("识别中...")
self.tagTwoLabel.setText("识别中...")
self.tagThreeLabel.setText("识别中...")
self.tagFourLabel.setText("识别中...")
self.tagFiveLabel.setText("识别中...")
if self.handle == 0:
QMessageBox.information(self, "No Handle", "No Handle")
self.queryStatusTag.setText("请选择句柄")
self.queryStatusTag.setStyleSheet("color:red")
return
gameImage = screen.grabWindow(
self.handle).toImage() # 直接截取vbox子窗口和DMM的UnityWnd
translatedCharH = gameImage.height(
) * config_dict['tagImageParams']['heightRatio']
translatedCharW = gameImage.width(
) * config_dict['tagImageParams']['widthRatio']
self.tagImageList = [
gameImage.copy(gameImage.width() * ratioCordinates['x'],
gameImage.height() * ratioCordinates['y'],
translatedCharW, translatedCharH).scaledToWidth(100)
for ratioCordinates in config_dict['tagImageParams']
['tagLocationRatio']
]
self.tagImagePixList = [
QtGui.QPixmap.fromImage(tagImage) for tagImage in self.tagImageList
]
self.tagImageItemList = [
QGraphicsPixmapItem(tagImagePix)
for tagImagePix in self.tagImagePixList
]
for i in range(len(self.tagImageSceneList)):
self.tagImageSceneList[i].addItem(self.tagImageItemList[i])
self.tagImageOneGraphicsView.setScene(self.tagImageSceneList[0])
self.tagImageTwoGraphicsView.setScene(self.tagImageSceneList[1])
self.tagImageThreeGraphicsView.setScene(self.tagImageSceneList[2])
self.tagImageFourGraphicsView.setScene(self.tagImageSceneList[3])
self.tagImageFiveGraphicsView.setScene(self.tagImageSceneList[4])
# tagImageToTagTypeRunnableList = []
# for i in range(5):
# tagImageToTagTypeRunnableList.append(tagImageToTagTypeRunnable(self.tagImageList[i], i, self))
try:
for i in range(5):
rawImage = self.tagImageList[i].convertToFormat(4)
w = rawImage.width()
h = rawImage.height()
ptr = rawImage.bits()
ptr.setsize(rawImage.byteCount())
preparedImage = np.array(ptr).reshape(h, w, 4) #此处完成转换
preparedImage = cv2.cvtColor(preparedImage, cv2.COLOR_BGRA2BGR)
tagType = "".join(
self.ocrInstance.ocr_for_single_line(preparedImage))
tagType = re.sub('[\x00-\xff，-]', '', tagType)
self.tagTypeList[i] = tagType
if i == 0:
self.tagOneLabel.setText(tagType)
if i == 1:
self.tagTwoLabel.setText(tagType)
if i == 2:
self.tagThreeLabel.setText(tagType)
if i == 3:
self.tagFourLabel.setText(tagType)
if i == 4:
self.tagFiveLabel.setText(tagType)
print('tagType %s' % i, tagType)
except Exception as e:
print(e)
pass
candidateStrategyListDict = {
'singleTagStrategyList': [],
'doubleTagStrategyList': []
}
for singleTagStrategy in strategyListDict['singleTagStrategyList']:
if singleTagStrategy['tag'] in self.tagTypeList:
candidateStrategyListDict['singleTagStrategyList'].append(
singleTagStrategy)
for doubleTagStrategy in strategyListDict['doubleTagStrategyList']:
if set(doubleTagStrategy['tagCombination']).issubset(
self.tagTypeList):
candidateStrategyListDict['doubleTagStrategyList'].append(
doubleTagStrategy)
print(candidateStrategyListDict)
self.singleTagStrategyListTempPlainTextEdit.clear()
self.doubleTagStrategyListTempPlainTextEdit.clear()
if len(candidateStrategyListDict['singleTagStrategyList']) == 0:
self.singleTagStrategyListTempPlainTextEdit.appendPlainText('无结果')
else:
for singleTagStrategy in candidateStrategyListDict[
'singleTagStrategyList']:
self.singleTagStrategyListTempPlainTextEdit.appendPlainText(
"选择%s可以锁定：\n" % singleTagStrategy['tag'])
for plausibleOperator in singleTagStrategy['plausibleList']:
self.singleTagStrategyListTempPlainTextEdit.appendPlainText(
"⭐%s %s" % (str((plausibleOperator['rarity'] + 1)),
plausibleOperator['name']))
if len(candidateStrategyListDict['doubleTagStrategyList']) == 0:
self.doubleTagStrategyListTempPlainTextEdit.appendPlainText('无结果')
else:
for doubleTagStrategy in candidateStrategyListDict[
'doubleTagStrategyList']:
self.doubleTagStrategyListTempPlainTextEdit.appendPlainText(
"选择%s + %s 可以锁定：\n" %
(doubleTagStrategy['tagCombination'][0],
doubleTagStrategy['tagCombination'][1]))
for plausibleOperator in doubleTagStrategy['plausibleList']:
self.doubleTagStrategyListTempPlainTextEdit.appendPlainText(
"⭐%s %s" % (str((plausibleOperator['rarity'] + 1)),
plausibleOperator['name']))
# for key in list(dataDict.keys()):
# try:
# processedTagTypeList = copy.deepcopy(self.tagTypeList[i])
# processedTagTypeList = list(filter(lambda item: item != "新手", processedTagTypeList))
# processedTagList = copy.deepcopy(dataDict[key]["tagList"])
# if dataDict[key]['position'] == "RANGED":
# processedTagList.append("远程位")
# else:
# processedTagList.append("近战位位")
# intersection = list(set(processedTagList) & set(self.tagTypeList))
# if len(intersection) != 0:
# candidateList.append(dataDict[key])
# except:
# # pass
# readableCandidateList = [candidate["name"] for candidate in candidateList]
# print(readableCandidateList)
def updateData(self):
url = "https://github.91chifun.workers.dev//https://raw.githubusercontent.com/Kengxxiao/ArknightsGameData/master/zh_CN/gamedata/excel/character_table.json"
newOTARunnable = OTARunnable(url)
QThreadPool.globalInstance().start(newOTARunnable)
# 这里可能会产生异步问题
dataDict = util.loadDataDict()
strategyListDict = util.config_loadStrategyListDict()
for w in place:
words.add(w)
place_con[place] = k
ocr = CnOcr(model_name='densenet-lite-gru')
d = d3dshot.create(capture_output="numpy")
time.sleep(1)
region = cfg['region']
region = region[0], region[1], region[0] + region[2], region[1] + region[3]
d.capture(region=region)
st = time.time()
while time.time() - st < 80:
frame = d.get_latest_frame()
if frame is None:
time.sleep(0.001)
continue
ocr_res = ocr.ocr_for_single_line(frame)
ocr_res = "".join(ocr_res)
if "，" in ocr_res:
ocr_res = ocr_res.split("，")[0]
fix_res = list(filter(lambda x: x in words, ocr_res))
fix_res = "".join(fix_res)
print(f'result: {fix_res} ocr result: {ocr_res}')
check = [(k, Levenshtein.distance(k, fix_res)) for k in place_con]
place, dis = sorted(check, key=lambda x: x[1])[0]
if dis <= 1:
con = place_con[place]
click_pos = cfg['postbox'][con]
print(f'click on {con}')
pyautogui.leftClick(click_pos[0], click_pos[1], interval=0.1, duration=0.1)
d.stop()
# -*- coding: utf-8 -*-
from cnocr import CnOcr # pip install cnocr # 中文OCR
import cv2
cn_ocr = CnOcr(root='cnocr_model')
# img = cv2.imread('data/tt15.png')
img = cv2.imread('data/tt16.png')
ocr_res = cn_ocr.ocr_for_single_line(img)
print('ocr result: %s' % ''.join(ocr_res))
def predict(file):
img_gray = io.imread(file, True)
img_gray = add_black_line(img_gray)
img_binary = get_binary_img(img_gray) #二值化图像
rows, cols = img_binary.shape
scale = 25
col_selem = morphology.rectangle(cols // scale,
1) # 用长cols//scale,宽1的滤波器进行腐蚀膨胀
row_selem = morphology.rectangle(1, rows //
scale) # 用长1，快rows//scale的滤波器进行腐蚀膨胀
img_cols = dil_ero(img_binary, col_selem) # 竖线图
img_rows = dil_ero(img_binary, row_selem) # 横线图
img_line = img_cols * img_rows # 有0的都取0 得到线图
img_dot = img_cols + img_rows # 有白的都取白 得到点图
# 画线图
plt.imshow(img_line, plt.cm.gray)
plt.show()
# 画点图
plt.imshow(img_dot, plt.cm.gray)
plt.show()
for i in range(rows):
for j in range(cols):
if img_dot[i, j] == 2:
img_dot[i, j] = 1
'''
点团浓缩为单个像素
'''
width = 7
idx = np.argwhere(img_dot == 0)
idx_unirow = list(np.unique(idx[:, 0]))
idx_unicol = list(np.unique(idx[:, 1]))
dot_rows = len(idx_unirow)
dot_cols = len(idx_unicol)
for i in range(dot_rows):
cur_row = idx_unirow[i]
for j in range(dot_cols):
cur_col = idx_unicol[j]
value = img_dot[cur_row, cur_col]
if value == 0:
for x in range(0, width + 1):
for y in range(0, width + 1):
if (not (x == 0 and y == 0)
) and cur_row + x < rows and cur_col + y < cols:
# print(i + x, ' ', j + y)
img_dot[cur_row + x, cur_col + y] = 1
'''
统一横纵坐标标准
'''
idx = np.argwhere(img_dot == 0) # 点的坐标
idx_unirow = list(np.unique(idx[:, 0]))
idx_unicol = list(np.unique(idx[:, 1]))
row_standard = []
for i in range(len(idx_unirow)):
each_unique_row = idx_unirow[i]
if i == 0:
row_standard.append(each_unique_row)
continue
if each_unique_row not in row_standard:
flag = True
for each_standard in row_standard:
difference = abs(each_unique_row - each_standard)
if difference <= 3:
flag = False
break
if flag:
row_standard.append(each_unique_row)
col_standard = []
for i in range(len(idx_unicol)):
each_unique_col = idx_unicol[i]
if i == 0:
col_standard.append(each_unique_col)
continue
if each_unique_col not in col_standard:
flag = True
for each_standard in col_standard:
difference = abs(each_unique_col - each_standard)
if difference <= 3:
flag = False
break
if flag:
col_standard.append(each_unique_col)
'''
对点的横纵坐标进行统一
'''
for i in range(len(idx)):
each_dot = idx[i]
for each_row_standard in row_standard:
row = each_dot[0]
row_difference = abs(each_row_standard - row)
if row_difference <= 3:
each_dot[0] = each_row_standard
break
for each_col_standard in col_standard:
col = each_dot[1]
col_difference = abs(each_col_standard - col)
if col_difference <= 3:
each_dot[1] = each_col_standard
break
idx = np.unique(idx, axis=0)
img_dot = np.ones((rows, cols))
for each_dot in idx:
row = each_dot[0]
col = each_dot[1]
img_dot[row, col] = 0
# 点图
plt.imshow(img_dot, plt.cm.gray)
plt.show()
'''对线的横纵坐标进行补线'''
# 统一横线
row_idx = np.argwhere(img_rows == 0)
for i in range(len(row_idx)):
each_row_dot = row_idx[i]
row = each_row_dot[0]
for each_row_standard in row_standard:
difference = abs(row - each_row_standard)
if difference <= 3:
col = each_row_dot[1]
img_rows[each_row_standard, col] = 0
break
# 统一竖线
col_idx = np.argwhere(img_cols == 0)
for i in range(len(col_idx)):
each_col_dot = col_idx[i]
col = each_col_dot[1]
for each_col_standard in col_standard:
difference = abs(col - each_col_standard)
if difference <= 3:
row = each_col_dot[0]
img_cols[row, each_col_standard] = 0
break
# 画线图
img_line = img_cols * img_line
plt.imshow(img_line, plt.cm.gray)
plt.show()
# 画点图
plt.imshow(img_dot, plt.cm.gray)
plt.show()
'''
按黑线切分单元格
'''
idx = np.argwhere(img_dot == 0) # 点的坐标
idx_unirow = list(np.unique(idx[:, 0]))
cell_items = []
for i in range(len(idx_unirow) - 1):
row_cur = idx_unirow[i] # 第一行横坐标
idx_row_cur = idx[idx[:, 0] == row_cur] # 当前行的所有点坐标
for j in range(len(idx_row_cur) - 1): # 遍历当前行的所有点坐标作为起点
# 检测左上角点是否可以作为起点
# 检测左边是否连续
col_cur = idx_row_cur[j][1]
row_next_test_1 = idx_unirow[i + 1]
black_line_test_1 = img_cols[row_cur:row_next_test_1, col_cur]
if np.sum(black_line_test_1) != 0:
# print('左上角点与下一行的像素和等于', np.sum(black_line_test_1),'失败')
continue
# 检测上边是否连续
col_next_text_2 = idx_row_cur[j + 1][1]
black_line_test_2 = img_rows[row_cur, col_cur:col_next_text_2]
if np.sum(black_line_test_2) != 0:
continue
for a in range(j + 1, len(idx_row_cur)): # 遍历当前行的当前点右边的所有点的坐标
col_next = idx_row_cur[a][1] # 当前行下一个点（右上角点）的纵坐标
idx_col_next = idx[idx[:, 1] == col_next] # 下一列的所有点的坐标
index = None
length = len(idx_col_next)
# 找到右上角的点在当前列的索引
for b in range(length):
if idx_col_next[b][0] == row_cur and idx_col_next[b][
1] == col_next:
index = b
break
# 检测右上角点是否可以作为起点
if index + 1 < length: # 如果这个起点不是这列的最下面的点
row_next_test_3 = idx_col_next[index +
1][0] # 右上角点下一行测试点的横坐标
black_line_test_3 = img_cols[row_cur:row_next_test_3,
col_next]
else:
continue
if np.sum(black_line_test_3) != 0:
continue
for c in range(index + 1, length):
row_next = idx_col_next[c][0] # 第三个点的横坐标
left_line = img_cols[row_cur:row_next, col_cur]
right_line = img_cols[row_cur:row_next, col_next]
if np.sum(left_line) != 0 or np.sum(right_line) != 0:
break
down_line = img_rows[row_next, col_cur:col_next]
if np.sum(down_line) == 0:
sub_img = img_binary[row_cur:row_next,
col_cur:col_next]
sub_item = Cell(sub_img, (row_cur, col_cur))
cell_items.append(sub_item)
break
break
'''更新切分'''
cell_items_new = []
for each_cell in cell_items:
result = cut(each_cell, idx_unirow)
if result:
for each_sub_item in result:
cell_items_new.append(each_sub_item)
else:
cell_items_new.append(each_cell)
x = []
y = []
for each in cell_items_new:
x.append(each.location[0])
y.append(each.location[1])
unique_x = np.unique(x)
unique_y = np.unique(y)
unique_x.sort()
unique_y.sort()
df = DataFrame(np.full((len(unique_x), len(unique_y)), np.nan))
ocr = CnOcr(model_name='densenet-lite-fc',
model_epoch=72,
root='local_models')
root = 'sub_cut_df'
t = 0
for each_cell in cell_items_new:
a, b = each_cell.location
c = a + each_cell.img.shape[0]
d = b + each_cell.img.shape[1]
t += 1
img = img_gray[a:c, b:d]
img = clean(img) # 去黑线
img = clean_white_vertical(img) # 去上下白边
img = clean_white_horizontal(img) # 去左右白边
img *= 255
row_index = np.argwhere(unique_x == each_cell.location[0])[0][0]
col_index = np.argwhere(unique_y == each_cell.location[1])[0][0]
dir = os.path.join(
root,
str(t) + '_(' + str(row_index) + ', ' + str(col_index) + ')' +
'[' + str(a) + ', ' + str(b) + ']' + '.jpg')
io.imsave(dir, img)
img = cv2.imdecode(np.fromfile(dir, dtype=np.uint8), 0)
height, width = img.shape
img = np.array(cv2.resize(img, (3 * width, 3 * height)))
cv2.imencode('.jpg', img)[1].tofile(dir)
try:
value = ocr.ocr_for_single_line(img)
value = ''.join(value)
except:
value = np.NAN
print(value)
df.iloc[row_index, col_index] = value
df.to_excel('result_df.xlsx', index=False)
class picture(QWidget):
def __init__(self):
super(picture, self).__init__()
self.resize(350, 350)
self.setWindowTitle("图片转文字")
self.label = QLabel(self)
# self.label.setText("显示图片")
self.label.setScaledContents(True)
self.label.setFixedSize(300, 200)
self.label.move(25, 60)
self.label.setStyleSheet(
"QLabel{background:white;}"
"QLabel{color:rgb(300,300,300,120);font-size:10px;font-weight:bold;font-family:宋体;}"
)
btn = QPushButton(self)
btn.setText("打开图片")
btn.move(135, 20)
btn.clicked.connect(self.openimage)
self.label_text = QLabel(self)
self.label_text.setFixedSize(300, 30)
self.label_text.move(25, 270)
self.label_text.setTextInteractionFlags(
Qt.TextSelectableByMouse) ###可复制
self.label_wait = QLabel(self)
self.label_wait.setFixedSize(300, 30)
self.label_wait.move(25, 300)
# 标签1的背景填充更改为True，否则无法显示背景
self.label_wait.setAutoFillBackground(True)
# # 实例化背景对象，进行相关背景颜色属性设置
# palette = QPalette()
# palette.setColor(QPalette.Window, Qt.green)
# # 标签1加载背景
# self.label_wait.setPalette(palette)
# 设置文本居中显示
self.label_wait.setAlignment(Qt.AlignCenter)
self.label_wait.setText('tips：识别过程可能会卡住，需几秒到几十秒不等')
self.std = CnStd()
self.cn_ocr = CnOcr()
def openimage(self):
imgName, imgType = QFileDialog.getOpenFileName(
self, "打开图片", "", "*.jpg;;*.png;;All Files(*)")
if imgName and imgType:
# 实例化背景对象，进行相关背景颜色属性设置
palette = QPalette()
palette.setColor(QPalette.Window, Qt.green)
# 标签1加载背景
self.label_wait.setPalette(palette)
box_info_list = self.std.detect(imgName)
result = ''
for box_info in box_info_list:
cropped_img = box_info['cropped_img'] # 检测出的文本框
# cv2.imshow('1', cropped_img)
# cv2.waitKey(0)
ocr_res = self.cn_ocr.ocr_for_single_line(cropped_img)
result += ''.join(ocr_res)
# print('ocr result: %s' % ''.join(ocr_res))
# print(result)
self.label_text.setText(result)
self.label_wait.setText('↑点击文字，ctrl+a全选、ctrl+c复制、ctrl+v粘贴')
jpg = QtGui.QPixmap(imgName).scaled(self.label.width(),
self.label.height())
self.label.setPixmap(jpg)
with open('history.txt', 'a', encoding='utf8') as f:
f.write(result + '\n')
print('初始化失败，未找到预加载模型')
return None
def has_chinese(word):
for ch in word:
if '\u4e00' <= ch <= '\u9fff':
return True
return False
if __name__ == '__main__':
ocr = CnOcr()
std = CnStd()
path = '/images/life.jpg'
img = cv2.imdecode(np.fromfile(path, dtype=np.uint8), -1)
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
img = np.array(img)
# res = ocr.ocr(img)
box_info_list = std.detect(img)
res = ''
for box_info in box_info_list:
cropped_img = box_info['cropped_img']
ocr_res = ocr.ocr_for_single_line(cropped_img)
res += ''.join(ocr_res) + '\n'
# print('ocr result: %s' % ''.join(ocr_res))
print("Predicted Chars:", res)
import mxnet as mx
from cnocr import CnOcr
ocr = CnOcr()
img_fp = 'examples/1.png'
img = mx.image.imread(img_fp, 1)
res = ocr.ocr_for_single_line(img)
print("Predicted Chars:", res)
text_list.append(''.join(res))
return text_list
if __name__ == '__main__':
ocr = CnOcr()
image = cv2.imread(r'try.png', cv2.IMREAD_GRAYSCALE)
print(image)
print(image.shape)
cv2.imshow('gray_image', image)
cv2.waitKey(0)
cv2.destroyAllWindows()
height_image, width_image = image.shape
_, binary_image = cv2.threshold(image, 150, 255, cv2.THRESH_BINARY_INV)
cv2.imshow('binary_image', binary_image)
cv2.waitKey(0)
cv2.destroyAllWindows()
height_projection = get_horizontal_projection(binary_image)
text_lines = get_text_lines(height_projection)
for line_index, text_line in enumerate(text_lines):
text_line_image = binary_image[text_line[0]:text_line[1],
0:width_image]
vertical_projection = get_vertical_projection(text_line_image)
text_words = get_text_word(vertical_projection)
text_line_word_image = image[text_line[0]:text_line[1],
text_words[0][0]:text_words[-1][1]]
cv2.imshow('text_line_word_image', text_line_word_image)
cv2.waitKey(0)
cv2.destroyAllWindows()
res = ocr.ocr_for_single_line(text_line_word_image)
print(''.join(res))
