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Merge branch 'dygraph' of https://github.com/PaddlePaddle/PaddleOCR into drrg_branch

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zhiminzhang0830
2022-10-10 15:56:08 +08:00
parent 6941fa5709 87fcbf6bba
commit 3ee146fa99
58 changed files with 2925 additions and 436 deletions
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tools/export_model.py
+2 -2
View File
@@ -77,7 +77,7 @@ def export_single_model(model,
elif arch_config["algorithm"] == "PREN":
other_shape = [
paddle.static.InputSpec(
shape=[None, 3, 64, 512], dtype="float32"),
shape=[None, 3, 64, 256], dtype="float32"),
]
model = to_static(model, input_spec=other_shape)
elif arch_config["model_type"] == "sr":
@@ -99,7 +99,7 @@ def export_single_model(model,
]
# print([None, 3, 32, 128])
model = to_static(model, input_spec=other_shape)
elif arch_config["algorithm"] in ["NRTR", "SPIN"]:
elif arch_config["algorithm"] in ["NRTR", "SPIN", 'RFL']:
other_shape = [
paddle.static.InputSpec(
shape=[None, 1, 32, 100], dtype="float32"),
tools/infer/predict_rec.py
+19 -1
View File
@@ -100,6 +100,14 @@ class TextRecognizer(object):
"use_space_char": args.use_space_char,
"rm_symbol": True
}
elif self.rec_algorithm == 'RFL':
postprocess_params = {
'name': 'RFLLabelDecode',
"character_dict_path": None,
"use_space_char": args.use_space_char
}
elif self.rec_algorithm == "PREN":
postprocess_params = {'name': 'PRENLabelDecode'}
self.postprocess_op = build_post_process(postprocess_params)
self.predictor, self.input_tensor, self.output_tensors, self.config = \
utility.create_predictor(args, 'rec', logger)
@@ -143,6 +151,16 @@ class TextRecognizer(object):
else:
norm_img = norm_img.astype(np.float32) / 128. - 1.
return norm_img
elif self.rec_algorithm == 'RFL':
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
resized_image = cv2.resize(
img, (imgW, imgH), interpolation=cv2.INTER_CUBIC)
resized_image = resized_image.astype('float32')
resized_image = resized_image / 255
resized_image = resized_image[np.newaxis, :]
resized_image -= 0.5
resized_image /= 0.5
return resized_image
assert imgC == img.shape[2]
imgW = int((imgH * max_wh_ratio))
@@ -384,7 +402,7 @@ class TextRecognizer(object):
self.rec_image_shape)
norm_img = norm_img[np.newaxis, :]
norm_img_batch.append(norm_img)
elif self.rec_algorithm == "VisionLAN":
elif self.rec_algorithm in ["VisionLAN", "PREN"]:
norm_img = self.resize_norm_img_vl(img_list[indices[ino]],
self.rec_image_shape)
norm_img = norm_img[np.newaxis, :]
tools/infer_rec.py
+10 -4
View File
@@ -97,7 +97,8 @@ def main():
elif config['Architecture']['algorithm'] == "SAR":
op[op_name]['keep_keys'] = ['image', 'valid_ratio']
elif config['Architecture']['algorithm'] == "RobustScanner":
op[op_name]['keep_keys'] = ['image', 'valid_ratio', 'word_positons']
op[op_name][
'keep_keys'] = ['image', 'valid_ratio', 'word_positons']
else:
op[op_name]['keep_keys'] = ['image']
transforms.append(op)
@@ -136,9 +137,10 @@ def main():
if config['Architecture']['algorithm'] == "RobustScanner":
valid_ratio = np.expand_dims(batch[1], axis=0)
word_positons = np.expand_dims(batch[2], axis=0)
img_metas = [paddle.to_tensor(valid_ratio),
paddle.to_tensor(word_positons),
]
img_metas = [
paddle.to_tensor(valid_ratio),
paddle.to_tensor(word_positons),
]
images = np.expand_dims(batch[0], axis=0)
images = paddle.to_tensor(images)
if config['Architecture']['algorithm'] == "SRN":
@@ -160,6 +162,10 @@ def main():
"score": float(post_result[key][0][1]),
}
info = json.dumps(rec_info, ensure_ascii=False)
elif isinstance(post_result, list) and isinstance(post_result[0],
int):
# for RFLearning CNT branch
info = str(post_result[0])
else:
if len(post_result[0]) >= 2:
info = post_result[0][0] + "\t" + str(post_result[0][1])
tools/program.py
+10 -4
View File
@@ -114,7 +114,7 @@ def merge_config(config, opts):
return config
def check_device(use_gpu, use_xpu=False, use_npu=False):
def check_device(use_gpu, use_xpu=False, use_npu=False, use_mlu=False):
"""
Log error and exit when set use_gpu=true in paddlepaddle
cpu version.
@@ -137,6 +137,9 @@ def check_device(use_gpu, use_xpu=False, use_npu=False):
if use_npu and not paddle.device.is_compiled_with_npu():
print(err.format("use_npu", "npu", "npu", "use_npu"))
sys.exit(1)
if use_mlu and not paddle.device.is_compiled_with_mlu():
print(err.format("use_mlu", "mlu", "mlu", "use_mlu"))
sys.exit(1)
except Exception as e:
pass
@@ -217,7 +220,7 @@ def train(config,
use_srn = config['Architecture']['algorithm'] == "SRN"
extra_input_models = [
"SRN", "NRTR", "SAR", "SEED", "SVTR", "SPIN", "VisionLAN",
"RobustScanner", 'DRRG'
"RobustScanner", "RFL", 'DRRG'
]
extra_input = False
if config['Architecture']['algorithm'] == 'Distillation':
@@ -618,6 +621,7 @@ def preprocess(is_train=False):
use_gpu = config['Global'].get('use_gpu', False)
use_xpu = config['Global'].get('use_xpu', False)
use_npu = config['Global'].get('use_npu', False)
use_mlu = config['Global'].get('use_mlu', False)
alg = config['Architecture']['algorithm']
assert alg in [
@@ -625,17 +629,19 @@ def preprocess(is_train=False):
'CLS', 'PGNet', 'Distillation', 'NRTR', 'TableAttn', 'SAR', 'PSE',
'SEED', 'SDMGR', 'LayoutXLM', 'LayoutLM', 'LayoutLMv2', 'PREN', 'FCE',
'SVTR', 'ViTSTR', 'ABINet', 'DB++', 'TableMaster', 'SPIN', 'VisionLAN',
'Gestalt', 'SLANet', 'RobustScanner', 'CT', 'DRRG'
'Gestalt', 'SLANet', 'RobustScanner', 'CT', 'RFL', 'DRRG'
]
if use_xpu:
device = 'xpu:{0}'.format(os.getenv('FLAGS_selected_xpus', 0))
elif use_npu:
device = 'npu:{0}'.format(os.getenv('FLAGS_selected_npus', 0))
elif use_mlu:
device = 'mlu:{0}'.format(os.getenv('FLAGS_selected_mlus', 0))
else:
device = 'gpu:{}'.format(dist.ParallelEnv()
.dev_id) if use_gpu else 'cpu'
check_device(use_gpu, use_xpu, use_npu)
check_device(use_gpu, use_xpu, use_npu, use_mlu)
device = paddle.set_device(device)
tools/train.py
+5 -4
View File
@@ -149,10 +149,11 @@ def main(config, device, logger, vdl_writer):
amp_level = config["Global"].get("amp_level", 'O2')
amp_custom_black_list = config['Global'].get('amp_custom_black_list', [])
if use_amp:
AMP_RELATED_FLAGS_SETTING = {
'FLAGS_cudnn_batchnorm_spatial_persistent': 1,
'FLAGS_max_inplace_grad_add': 8,
}
AMP_RELATED_FLAGS_SETTING = {'FLAGS_max_inplace_grad_add': 8, }
if paddle.is_compiled_with_cuda():
AMP_RELATED_FLAGS_SETTING.update({
'FLAGS_cudnn_batchnorm_spatial_persistent': 1
})
paddle.fluid.set_flags(AMP_RELATED_FLAGS_SETTING)
scale_loss = config["Global"].get("scale_loss", 1.0)
use_dynamic_loss_scaling = config["Global"].get(