a, b, newBoxes = show(jpgPath[9])
print(newBoxes)
#anchors = cluster.anchors
# anchors = '8,9, 8,18, 8,31, 8,59, 8,124, 8,351, 8,509, 8,605, 8,800'
anchors = '8,24, 8,31, 8,37, 8,42, 8,47, 8,53, 8,58, 8,65, 8,73'
anchors = [float(x) for x in anchors.split(',')]
anchors = np.array(anchors).reshape(-1, 2)
num_anchors = len(anchors)
class_names = [
'none',
'text',
] ##text
num_classes = len(class_names)
textModel = yolo_text(num_classes, anchors, train=True)
textModel.load_weights(
'F:/project/chineseocrmodels/models/text.h5') ##加载预训练模型权重
trainLoad = data_generator(jpgPath[:num_train], anchors, num_classes, splitW)
testLoad = data_generator(jpgPath[num_train:], anchors, num_classes, splitW)
log_dir = "logs/"
batch_size = 64
# textModel.summary() #打印模型概述信息
epochs = 100
print(len(textModel.layers))
textModel.trainable = True
"""
from config import kerasTextModel,IMGSIZE,keras_anchors,class_names,GPU,GPUID
from text.keras_yolo3 import yolo_text,box_layer,K
from helper.image import resize_im,letterbox_image
from PIL import Image
import numpy as np
import tensorflow as tf
graph = tf.get_default_graph()##解决web.py 相关报错问题
anchors = [float(x) for x in keras_anchors.split(',')]
anchors = np.array(anchors).reshape(-1, 2)
num_anchors = len(anchors)
num_classes = len(class_names)
textModel = yolo_text(num_classes,anchors)
textModel.load_weights(kerasTextModel)
sess = K.get_session()
image_shape = K.placeholder(shape=(2, ))##图像原尺寸:h,w
input_shape = K.placeholder(shape=(2, ))##图像resize尺寸:h,w
box_score = box_layer([*textModel.output,image_shape,input_shape],anchors, num_classes)
def text_detect(img,prob = 0.05):
im = Image.fromarray(img)
scale = IMGSIZE[0]
w,h = im.size
w_,h_ = resize_im(w,h, scale=scale, max_scale=2048)##短边固定为608,长边max_scale<4000