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fix infer

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This commit is contained in:
LDOUBLEV 2021-10-09 15:48:16 +08:00
parent 50020a8ef9
commit c342b7a013
1 changed files with 14 additions and 12 deletions
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26
tools/infer_kie.py
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@ -47,9 +47,9 @@ def read_class_list(filepath):
return dict return dict
def draw_kie_result(batch, node, idx_to_cls): def draw_kie_result(batch, node, idx_to_cls, count):
img = batch[-2] img = batch[6].copy()
boxes = batch[-1] boxes = batch[7]
h, w = img.shape[:2] h, w = img.shape[:2]
pred_img = np.ones((h, w * 2, 3), dtype=np.uint8) * 255 pred_img = np.ones((h, w * 2, 3), dtype=np.uint8) * 255
max_value, max_idx = paddle.max(node, -1), paddle.argmax(node, -1) max_value, max_idx = paddle.max(node, -1), paddle.argmax(node, -1)
@ -77,11 +77,15 @@ def draw_kie_result(batch, node, idx_to_cls):
text = pred_label + '(' + pred_score + ')' text = pred_label + '(' + pred_score + ')'
cv2.putText(pred_img, text, (x_min * 2, y_min), cv2.putText(pred_img, text, (x_min * 2, y_min),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 0, 0), 1) cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 0, 0), 1)
vis_img = np.ones((h, w * 3, 3), dtype=np.uint8) * 255 vis_img = np.ones((h, w * 3, 3), dtype=np.uint8) * 255
vis_img[:, :w] = img vis_img[:, :w] = img
vis_img[:, w:] = pred_img vis_img[:, w:] = pred_img
return vis_img save_kie_path = os.path.dirname(config['Global']['save_res_path']) + "/kie_results/"
if not os.path.exists(save_kie_path):
os.makedirs(save_kie_path)
save_path = os.path.join(save_kie_path, str(count) + ".png")
cv2.imwrite(save_path, vis_img)
logger.info("The Kie Image saved in {}".format(save_path))
def main(): def main():
@ -89,7 +93,6 @@ def main():
# build model # build model
model = build_model(config['Architecture']) model = build_model(config['Architecture'])
init_model(config, model, logger) init_model(config, model, logger)
# create data ops # create data ops
@ -97,6 +100,8 @@ def main():
for op in config['Eval']['dataset']['transforms']: for op in config['Eval']['dataset']['transforms']:
transforms.append(op) transforms.append(op)
data_dir = config['Eval']['dataset']['data_dir']
ops = create_operators(transforms, global_config) ops = create_operators(transforms, global_config)
save_res_path = config['Global']['save_res_path'] save_res_path = config['Global']['save_res_path']
@ -109,11 +114,10 @@ def main():
with open(save_res_path, "wb") as fout: with open(save_res_path, "wb") as fout:
with open(config['Global']['infer_img'], "rb") as f: with open(config['Global']['infer_img'], "rb") as f:
lines = f.readlines() lines = f.readlines()
for data_line in lines: for index, data_line in enumerate(lines):
data_line = data_line.decode('utf-8') data_line = data_line.decode('utf-8')
substr = data_line.strip("\n").split("\t") substr = data_line.strip("\n").split("\t")
img_path, label = "/Users/hongyongjie/project/PaddleOCR/train_data/wildreceipt/" + substr[ img_path, label = data_dir + "/" + substr[0], substr[1]
0], substr[1]
data = {'img_path': img_path, 'label': label} data = {'img_path': img_path, 'label': label}
with open(data['img_path'], 'rb') as f: with open(data['img_path'], 'rb') as f:
img = f.read() img = f.read()
@ -126,9 +130,7 @@ def main():
batch[i], axis=0)) batch[i], axis=0))
node, edge = model(batch_pred) node, edge = model(batch_pred)
node = F.softmax(node, -1) node = F.softmax(node, -1)
img = draw_kie_result(batch, node, idx_to_cls) draw_kie_result(batch, node, idx_to_cls, index)
cv2.imwrite('1.png', img)
exit()
logger.info("success!") logger.info("success!")