diff --git a/doc/doc_en/quickstart_en.md b/doc/doc_en/quickstart_en.md
index d7aeb7773021aa6cf8f4d71298588915e5938fab..c678dc47625f4289a93621144bf5577b059d52b3 100644
--- a/doc/doc_en/quickstart_en.md
+++ b/doc/doc_en/quickstart_en.md
@@ -119,7 +119,18 @@ If you do not use the provided test image, you can replace the following `--imag
['PAIN', 0.9934559464454651]
```
-If you need to use the 2.0 model, please specify the parameter `--ocr_version PP-OCR`, paddleocr uses the PP-OCRv3 model by default(`--ocr_version PP-OCRv3`). More whl package usage can be found in [whl package](./whl_en.md)
+**Version**
+paddleocr uses the PP-OCRv3 model by default(`--ocr_version PP-OCRv3`). If you want to use other versions, you can set the parameter `--ocr_version`, the specific version description is as follows:
+| version name | description |
+| --- | --- |
+| PP-OCRv3 | support Chinese and English detection and recognition, direction classifier, support multilingual recognition |
+| PP-OCRv2 | only supports Chinese and English detection and recognition, direction classifier, multilingual model is not updated |
+| PP-OCR | support Chinese and English detection and recognition, direction classifier, support multilingual recognition |
+
+If you want to add your own trained model, you can add model links and keys in [paddleocr](../../paddleocr.py) and recompile.
+
+More whl package usage can be found in [whl package](./whl_en.md)
+
#### 2.1.2 Multi-language Model
diff --git a/paddleocr.py b/paddleocr.py
index a1265f79def7018a5586be954127e5b7fdba011e..470dc60da3b15195bcd401aff5e50be5a2cfd13e 100644
--- a/paddleocr.py
+++ b/paddleocr.py
@@ -154,7 +154,13 @@ MODEL_URLS = {
'https://paddleocr.bj.bcebos.com/PP-OCRv2/chinese/ch_PP-OCRv2_rec_infer.tar',
'dict_path': './ppocr/utils/ppocr_keys_v1.txt'
}
- }
+ },
+ 'cls': {
+ 'ch': {
+ 'url':
+ 'https://paddleocr.bj.bcebos.com/dygraph_v2.0/ch/ch_ppocr_mobile_v2.0_cls_infer.tar',
+ }
+ },
},
'PP-OCR': {
'det': {
diff --git a/ppocr/data/imaug/__init__.py b/ppocr/data/imaug/__init__.py
index 2dbc92a7037c58b09753330e9c5f1b9791252ef6..88c9603fb00a315e9df22dec27ac850c277089ec 100644
--- a/ppocr/data/imaug/__init__.py
+++ b/ppocr/data/imaug/__init__.py
@@ -22,6 +22,7 @@ from .make_shrink_map import MakeShrinkMap
from .random_crop_data import EastRandomCropData, RandomCropImgMask
from .make_pse_gt import MakePseGt
+
from .rec_img_aug import RecAug, RecConAug, RecResizeImg, ClsResizeImg, \
SRNRecResizeImg, GrayRecResizeImg, SARRecResizeImg, PRENResizeImg
from .ssl_img_aug import SSLRotateResize
diff --git a/ppocr/data/imaug/rec_img_aug.py b/ppocr/data/imaug/rec_img_aug.py
index 0697baf436fa1f345bbd33c7e0847be0d8f1df8c..d3120f595052d95a7abd7bb347c841e5628d43fb 100644
--- a/ppocr/data/imaug/rec_img_aug.py
+++ b/ppocr/data/imaug/rec_img_aug.py
@@ -22,13 +22,74 @@ from .text_image_aug import tia_perspective, tia_stretch, tia_distort
class RecAug(object):
- def __init__(self, use_tia=True, aug_prob=0.4, **kwargs):
- self.use_tia = use_tia
- self.aug_prob = aug_prob
+ def __init__(self,
+ tia_prob=0.4,
+ crop_prob=0.4,
+ reverse_prob=0.4,
+ noise_prob=0.4,
+ jitter_prob=0.4,
+ blur_prob=0.4,
+ hsv_aug_prob=0.4,
+ **kwargs):
+ self.tia_prob = tia_prob
+ self.bda = BaseDataAugmentation(crop_prob, reverse_prob, noise_prob,
+ jitter_prob, blur_prob, hsv_aug_prob)
def __call__(self, data):
img = data['image']
- img = warp(img, 10, self.use_tia, self.aug_prob)
+ h, w, _ = img.shape
+
+ # tia
+ if random.random() <= self.tia_prob:
+ if h >= 20 and w >= 20:
+ img = tia_distort(img, random.randint(3, 6))
+ img = tia_stretch(img, random.randint(3, 6))
+ img = tia_perspective(img)
+
+ # bda
+ data['image'] = img
+ data = self.bda(data)
+ return data
+
+
+class BaseDataAugmentation(object):
+ def __init__(self,
+ crop_prob=0.4,
+ reverse_prob=0.4,
+ noise_prob=0.4,
+ jitter_prob=0.4,
+ blur_prob=0.4,
+ hsv_aug_prob=0.4,
+ **kwargs):
+ self.crop_prob = crop_prob
+ self.reverse_prob = reverse_prob
+ self.noise_prob = noise_prob
+ self.jitter_prob = jitter_prob
+ self.blur_prob = blur_prob
+ self.hsv_aug_prob = hsv_aug_prob
+
+ def __call__(self, data):
+ img = data['image']
+ h, w, _ = img.shape
+
+ if random.random() <= self.crop_prob and h >= 20 and w >= 20:
+ img = get_crop(img)
+
+ if random.random() <= self.blur_prob:
+ img = blur(img)
+
+ if random.random() <= self.hsv_aug_prob:
+ img = hsv_aug(img)
+
+ if random.random() <= self.jitter_prob:
+ img = jitter(img)
+
+ if random.random() <= self.noise_prob:
+ img = add_gasuss_noise(img)
+
+ if random.random() <= self.reverse_prob:
+ img = 255 - img
+
data['image'] = img
return data
@@ -370,7 +431,7 @@ def flag():
return 1 if random.random() > 0.5000001 else -1
-def cvtColor(img):
+def hsv_aug(img):
"""
cvtColor
"""
@@ -438,50 +499,6 @@ def get_crop(image):
return crop_img
-class Config:
- """
- Config
- """
-
- def __init__(self, use_tia):
- self.anglex = random.random() * 30
- self.angley = random.random() * 15
- self.anglez = random.random() * 10
- self.fov = 42
- self.r = 0
- self.shearx = random.random() * 0.3
- self.sheary = random.random() * 0.05
- self.borderMode = cv2.BORDER_REPLICATE
- self.use_tia = use_tia
-
- def make(self, w, h, ang):
- """
- make
- """
- self.anglex = random.random() * 5 * flag()
- self.angley = random.random() * 5 * flag()
- self.anglez = -1 * random.random() * int(ang) * flag()
- self.fov = 42
- self.r = 0
- self.shearx = 0
- self.sheary = 0
- self.borderMode = cv2.BORDER_REPLICATE
- self.w = w
- self.h = h
-
- self.perspective = self.use_tia
- self.stretch = self.use_tia
- self.distort = self.use_tia
-
- self.crop = True
- self.affine = False
- self.reverse = True
- self.noise = True
- self.jitter = True
- self.blur = True
- self.color = True
-
-
def rad(x):
"""
rad
@@ -565,48 +582,3 @@ def get_warpAffine(config):
rz = np.array([[np.cos(rad(anglez)), np.sin(rad(anglez)), 0],
[-np.sin(rad(anglez)), np.cos(rad(anglez)), 0]], np.float32)
return rz
-
-
-def warp(img, ang, use_tia=True, prob=0.4):
- """
- warp
- """
- h, w, _ = img.shape
- config = Config(use_tia=use_tia)
- config.make(w, h, ang)
- new_img = img
-
- if config.distort:
- img_height, img_width = img.shape[0:2]
- if random.random() <= prob and img_height >= 20 and img_width >= 20:
- new_img = tia_distort(new_img, random.randint(3, 6))
-
- if config.stretch:
- img_height, img_width = img.shape[0:2]
- if random.random() <= prob and img_height >= 20 and img_width >= 20:
- new_img = tia_stretch(new_img, random.randint(3, 6))
-
- if config.perspective:
- if random.random() <= prob:
- new_img = tia_perspective(new_img)
-
- if config.crop:
- img_height, img_width = img.shape[0:2]
- if random.random() <= prob and img_height >= 20 and img_width >= 20:
- new_img = get_crop(new_img)
-
- if config.blur:
- if random.random() <= prob:
- new_img = blur(new_img)
- if config.color:
- if random.random() <= prob:
- new_img = cvtColor(new_img)
- if config.jitter:
- new_img = jitter(new_img)
- if config.noise:
- if random.random() <= prob:
- new_img = add_gasuss_noise(new_img)
- if config.reverse:
- if random.random() <= prob:
- new_img = 255 - new_img
- return new_img
diff --git a/ppocr/data/simple_dataset.py b/ppocr/data/simple_dataset.py
index b5da9b8898423facf888839f941dff01caa03643..402f1e38fed9e32722e2dd160f10f779028807a3 100644
--- a/ppocr/data/simple_dataset.py
+++ b/ppocr/data/simple_dataset.py
@@ -33,7 +33,7 @@ class SimpleDataSet(Dataset):
self.delimiter = dataset_config.get('delimiter', '\t')
label_file_list = dataset_config.pop('label_file_list')
data_source_num = len(label_file_list)
- ratio_list = dataset_config.get("ratio_list", [1.0])
+ ratio_list = dataset_config.get("ratio_list", 1.0)
if isinstance(ratio_list, (float, int)):
ratio_list = [float(ratio_list)] * int(data_source_num)
diff --git a/ppstructure/table/predict_table.py b/ppstructure/table/predict_table.py
index 402d6c24189d044e2ee6d359edef8624d4aae145..aa05459589208dde66a6710322593d091af41325 100644
--- a/ppstructure/table/predict_table.py
+++ b/ppstructure/table/predict_table.py
@@ -28,6 +28,7 @@ import numpy as np
import time
import tools.infer.predict_rec as predict_rec
import tools.infer.predict_det as predict_det
+import tools.infer.utility as utility
from ppocr.utils.utility import get_image_file_list, check_and_read_gif
from ppocr.utils.logging import get_logger
from ppstructure.table.matcher import distance, compute_iou
@@ -59,11 +60,37 @@ class TableSystem(object):
self.text_recognizer = predict_rec.TextRecognizer(
args) if text_recognizer is None else text_recognizer
self.table_structurer = predict_strture.TableStructurer(args)
+ self.benchmark = args.benchmark
+ self.predictor, self.input_tensor, self.output_tensors, self.config = utility.create_predictor(
+ args, 'table', logger)
+ if args.benchmark:
+ import auto_log
+ pid = os.getpid()
+ gpu_id = utility.get_infer_gpuid()
+ self.autolog = auto_log.AutoLogger(
+ model_name="table",
+ model_precision=args.precision,
+ batch_size=1,
+ data_shape="dynamic",
+ save_path=None, #args.save_log_path,
+ inference_config=self.config,
+ pids=pid,
+ process_name=None,
+ gpu_ids=gpu_id if args.use_gpu else None,
+ time_keys=[
+ 'preprocess_time', 'inference_time', 'postprocess_time'
+ ],
+ warmup=0,
+ logger=logger)
def __call__(self, img, return_ocr_result_in_table=False):
result = dict()
ori_im = img.copy()
+ if self.benchmark:
+ self.autolog.times.start()
structure_res, elapse = self.table_structurer(copy.deepcopy(img))
+ if self.benchmark:
+ self.autolog.times.stamp()
dt_boxes, elapse = self.text_detector(copy.deepcopy(img))
dt_boxes = sorted_boxes(dt_boxes)
if return_ocr_result_in_table:
@@ -77,13 +104,11 @@ class TableSystem(object):
box = [x_min, y_min, x_max, y_max]
r_boxes.append(box)
dt_boxes = np.array(r_boxes)
-
logger.debug("dt_boxes num : {}, elapse : {}".format(
len(dt_boxes), elapse))
if dt_boxes is None:
return None, None
img_crop_list = []
-
for i in range(len(dt_boxes)):
det_box = dt_boxes[i]
x0, y0, x1, y1 = expand(2, det_box, ori_im.shape)
@@ -92,10 +117,14 @@ class TableSystem(object):
rec_res, elapse = self.text_recognizer(img_crop_list)
logger.debug("rec_res num : {}, elapse : {}".format(
len(rec_res), elapse))
+ if self.benchmark:
+ self.autolog.times.stamp()
if return_ocr_result_in_table:
result['rec_res'] = rec_res
pred_html, pred = self.rebuild_table(structure_res, dt_boxes, rec_res)
result['html'] = pred_html
+ if self.benchmark:
+ self.autolog.times.end(stamp=True)
return result
def rebuild_table(self, structure_res, dt_boxes, rec_res):
@@ -213,6 +242,8 @@ def main(args):
logger.info('excel saved to {}'.format(excel_path))
elapse = time.time() - starttime
logger.info("Predict time : {:.3f}s".format(elapse))
+ if args.benchmark:
+ text_sys.autolog.report()
if __name__ == "__main__":
diff --git a/test_tipc/common_func.sh b/test_tipc/common_func.sh
index 85dfe217253bb1d4c8b92f17d26f138121a2a198..f7d8a1e04adee9d32332eda8cb5913bbaf168481 100644
--- a/test_tipc/common_func.sh
+++ b/test_tipc/common_func.sh
@@ -57,10 +57,11 @@ function status_check(){
last_status=$1 # the exit code
run_command=$2
run_log=$3
+ model_name=$4
if [ $last_status -eq 0 ]; then
- echo -e "\033[33m Run successfully with command - ${run_command}! \033[0m" | tee -a ${run_log}
+ echo -e "\033[33m Run successfully with command - ${model_name} - ${run_command}! \033[0m" | tee -a ${run_log}
else
- echo -e "\033[33m Run failed with command - ${run_command}! \033[0m" | tee -a ${run_log}
+ echo -e "\033[33m Run failed with command - ${model_name} - ${run_command}! \033[0m" | tee -a ${run_log}
fi
}
diff --git a/test_tipc/configs/ch_PP-OCRv2_det_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv2_det_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt
index 1aad65b687992155133ed11533a14f642510361d..ccc9e5ced086c2c617359bafdc8772fe92eab8fa 100644
--- a/test_tipc/configs/ch_PP-OCRv2_det_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt
+++ b/test_tipc/configs/ch_PP-OCRv2_det_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt
@@ -1,5 +1,5 @@
===========================kl_quant_params===========================
-model_name:PPOCRv2_ocr_det_kl
+model_name:ch_PP-OCRv2_det_KL
python:python3.7
Global.pretrained_model:null
Global.save_inference_dir:null
@@ -8,10 +8,10 @@ infer_export:deploy/slim/quantization/quant_kl.py -c configs/det/ch_PP-OCRv2/ch_
infer_quant:True
inference:tools/infer/predict_det.py
--use_gpu:False|True
---enable_mkldnn:True
---cpu_threads:1|6
+--enable_mkldnn:False
+--cpu_threads:6
--rec_batch_num:1
---use_tensorrt:False|True
+--use_tensorrt:False
--precision:int8
--det_model_dir:
--image_dir:./inference/ch_det_data_50/all-sum-510/
diff --git a/test_tipc/configs/ch_PP-OCRv2_rec_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv2_rec_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt
index 083a3ae26e726e290ffde4095821cbf3c40f7178..c30e0858efda4df8f9912183c5c31b56413a5252 100644
--- a/test_tipc/configs/ch_PP-OCRv2_rec_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt
+++ b/test_tipc/configs/ch_PP-OCRv2_rec_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt
@@ -1,17 +1,17 @@
===========================kl_quant_params===========================
-model_name:PPOCRv2_ocr_rec_kl
+model_name:ch_PP-OCRv2_rec_KL
python:python3.7
Global.pretrained_model:null
Global.save_inference_dir:null
infer_model:./inference/ch_PP-OCRv2_rec_infer/
infer_export:deploy/slim/quantization/quant_kl.py -c test_tipc/configs/ch_PP-OCRv2_rec/ch_PP-OCRv2_rec_distillation.yml -o
infer_quant:True
-inference:tools/infer/predict_rec.py
+inference:tools/infer/predict_rec.py --rec_image_shape="3,32,320"
--use_gpu:False|True
---enable_mkldnn:False|True
---cpu_threads:1|6
+--enable_mkldnn:False
+--cpu_threads:6
--rec_batch_num:1|6
---use_tensorrt:True
+--use_tensorrt:False
--precision:int8
--rec_model_dir:
--image_dir:./inference/rec_inference
diff --git a/test_tipc/configs/ch_PP-OCRv2_rec_PACT/train_infer_python.txt b/test_tipc/configs/ch_PP-OCRv2_rec_PACT/train_infer_python.txt
index 416832681794d32347d7c3bb36807787a83ff1d2..0ac75eff07a5ed4c17d7fdbe554fd4b5c0f11aed 100644
--- a/test_tipc/configs/ch_PP-OCRv2_rec_PACT/train_infer_python.txt
+++ b/test_tipc/configs/ch_PP-OCRv2_rec_PACT/train_infer_python.txt
@@ -4,7 +4,7 @@ python:python3.7
gpu_list:0|0,1
Global.use_gpu:True|True
Global.auto_cast:fp32
-Global.epoch_num:lite_train_lite_infer=6|whole_train_whole_infer=50
+Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=50
Global.save_model_dir:./output/
Train.loader.batch_size_per_card:lite_train_lite_infer=16|whole_train_whole_infer=128
Global.pretrained_model:pretrain_models/ch_PP-OCRv2_rec_train/best_accuracy
diff --git a/test_tipc/configs/ch_PP-OCRv3_det_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv3_det_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt
index e4a3aa6c61899adff18e69da2777f07ada8cbaaa..c27e08a64075e15e4fbd8d4ffab7001752365417 100644
--- a/test_tipc/configs/ch_PP-OCRv3_det_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt
+++ b/test_tipc/configs/ch_PP-OCRv3_det_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt
@@ -1,5 +1,5 @@
===========================kl_quant_params===========================
-model_name:PPOCRv3_ocr_det_kl
+model_name:ch_PP-OCRv3_det_KL
python:python3.7
Global.pretrained_model:null
Global.save_inference_dir:null
@@ -8,10 +8,10 @@ infer_export:deploy/slim/quantization/quant_kl.py -c configs/det/ch_PP-OCRv3/ch_
infer_quant:True
inference:tools/infer/predict_det.py
--use_gpu:False|True
---enable_mkldnn:True
---cpu_threads:1|6
+--enable_mkldnn:False
+--cpu_threads:6
--rec_batch_num:1
---use_tensorrt:False|True
+--use_tensorrt:False
--precision:int8
--det_model_dir:
--image_dir:./inference/ch_det_data_50/all-sum-510/
diff --git a/test_tipc/configs/ch_PP-OCRv3_rec_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_PP-OCRv3_rec_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt
index 51ad29a4edf81163a027f93ef1cb7f7c3b4168fd..d1a8c7c00137661bb1b5cced46f7616877f0b0a2 100644
--- a/test_tipc/configs/ch_PP-OCRv3_rec_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt
+++ b/test_tipc/configs/ch_PP-OCRv3_rec_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt
@@ -1,17 +1,17 @@
===========================kl_quant_params===========================
-model_name:PPOCRv3_ocr_rec_kl
+model_name:ch_PP-OCRv3_rec_KL
python:python3.7
-Global.pretrained_model:null
+Global.pretrained_model:
Global.save_inference_dir:null
infer_model:./inference/ch_PP-OCRv3_rec_infer/
infer_export:deploy/slim/quantization/quant_kl.py -c test_tipc/configs/ch_PP-OCRv3_rec/ch_PP-OCRv3_rec_distillation.yml -o
infer_quant:True
inference:tools/infer/predict_rec.py --rec_image_shape="3,48,320"
--use_gpu:False|True
---enable_mkldnn:False|True
---cpu_threads:1|6
+--enable_mkldnn:False
+--cpu_threads:6
--rec_batch_num:1|6
---use_tensorrt:True
+--use_tensorrt:False
--precision:int8
--rec_model_dir:
--image_dir:./inference/rec_inference
diff --git a/test_tipc/configs/ch_PP-OCRv3_rec_PACT/train_infer_python.txt b/test_tipc/configs/ch_PP-OCRv3_rec_PACT/train_infer_python.txt
index f26b86290af5f57569156c9329bc63c1c0b3a675..24469a91cfa0fa7d26ff24dba13c9c7e78a5ca10 100644
--- a/test_tipc/configs/ch_PP-OCRv3_rec_PACT/train_infer_python.txt
+++ b/test_tipc/configs/ch_PP-OCRv3_rec_PACT/train_infer_python.txt
@@ -4,7 +4,7 @@ python:python3.7
gpu_list:0|0,1
Global.use_gpu:True|True
Global.auto_cast:fp32
-Global.epoch_num:lite_train_lite_infer=6|whole_train_whole_infer=50
+Global.epoch_num:lite_train_lite_infer=1|whole_train_whole_infer=50
Global.save_model_dir:./output/
Train.loader.batch_size_per_card:lite_train_lite_infer=16|whole_train_whole_infer=128
Global.pretrained_model:pretrain_models/ch_PP-OCRv3_rec_train/best_accuracy
diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_det_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_det_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt
index 1039dcad06d63bb1fc1a47b7cc4760cd8d75ed63..2bdec848833b6cf3799370b0337fa00f185a94d5 100644
--- a/test_tipc/configs/ch_ppocr_mobile_v2.0_det_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt
+++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_det_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt
@@ -8,10 +8,10 @@ infer_export:deploy/slim/quantization/quant_kl.py -c configs/det/ch_ppocr_v2.0/c
infer_quant:True
inference:tools/infer/predict_det.py
--use_gpu:False|True
---enable_mkldnn:True
---cpu_threads:1|6
+--enable_mkldnn:False
+--cpu_threads:6
--rec_batch_num:1
---use_tensorrt:False|True
+--use_tensorrt:False
--precision:int8
--det_model_dir:
--image_dir:./inference/ch_det_data_50/all-sum-510/
diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_det_PACT/train_infer_python.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_det_PACT/train_infer_python.txt
index 522f30d14b952d3d2da5ee8232b4b175d909d9a4..04c8d0e194b687f58da1c449a6a0d8d9c1acd25e 100644
--- a/test_tipc/configs/ch_ppocr_mobile_v2.0_det_PACT/train_infer_python.txt
+++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_det_PACT/train_infer_python.txt
@@ -4,7 +4,7 @@ python:python3.7
gpu_list:0|0,1
Global.use_gpu:True|True
Global.auto_cast:null
-Global.epoch_num:lite_train_lite_infer=20|whole_train_whole_infer=50
+Global.epoch_num:lite_train_lite_infer=2|whole_train_whole_infer=50
Global.save_model_dir:./output/
Train.loader.batch_size_per_card:lite_train_lite_infer=2|whole_train_whole_infer=4
Global.pretrained_model:null
diff --git a/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt
index 4b77994f3f68c196b4d6e7a16eb44ec5fdef0d9e..f63fe4c2bb6a17353ecb008d83e2bee9d38aec23 100644
--- a/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt
+++ b/test_tipc/configs/ch_ppocr_mobile_v2.0_rec_KL/model_linux_gpu_normal_normal_infer_python_linux_gpu_cpu.txt
@@ -6,12 +6,12 @@ Global.save_inference_dir:null
infer_model:./inference/ch_ppocr_mobile_v2.0_rec_infer/
infer_export:deploy/slim/quantization/quant_kl.py -c test_tipc/configs/ch_ppocr_mobile_v2.0_rec_KL/rec_chinese_lite_train_v2.0.yml -o
infer_quant:True
-inference:tools/infer/predict_rec.py
+inference:tools/infer/predict_rec.py --rec_image_shape="3,32,320"
--use_gpu:False|True
---enable_mkldnn:True
---cpu_threads:1|6
+--enable_mkldnn:False
+--cpu_threads:6
--rec_batch_num:1
---use_tensorrt:False|True
+--use_tensorrt:False
--precision:int8
--rec_model_dir:
--image_dir:./inference/rec_inference