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PaddleOCR
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delete fluid

This commit is contained in:
WenmuZhou 2020-12-21 17:13:32 +08:00
parent 59af7359be
commit 3a0090dc00
5 changed files with 23 additions and 26 deletions
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44
ppocr/losses/det_sast_loss.py
View File

@ -19,7 +19,6 @@ from __future__ import print_function
import paddle
from paddle import nn
from .det_basic_loss import DiceLoss
import paddle.fluid as fluid
import numpy as np
@ -27,9 +26,7 @@ class SASTLoss(nn.Layer):
"""
"""
def __init__(self,
eps=1e-6,
**kwargs):
def __init__(self, eps=1e-6, **kwargs):
super(SASTLoss, self).__init__()
self.dice_loss = DiceLoss(eps=eps)
@ -39,7 +36,7 @@ class SASTLoss(nn.Layer):
tcl_mask: N x 128 x 1
tcl_label: N x X list or LoDTensor
"""
f_score = predicts['f_score']
f_border = predicts['f_border']
f_tvo = predicts['f_tvo']
@ -53,15 +50,17 @@ class SASTLoss(nn.Layer):
score_loss = 1.0 - 2 * intersection / (union + 1e-5)
#border loss
l_border_split, l_border_norm = paddle.split(l_border, num_or_sections=[4, 1], axis=1)
l_border_split, l_border_norm = paddle.split(
l_border, num_or_sections=[4, 1], axis=1)
f_border_split = f_border
border_ex_shape = l_border_norm.shape * np.array([1, 4, 1, 1])
l_border_norm_split = paddle.expand(x=l_border_norm, shape=border_ex_shape)
l_border_score = paddle.expand(x=l_score, shape=border_ex_shape)
l_border_mask = paddle.expand(x=l_mask, shape=border_ex_shape)
l_border_norm_split = paddle.expand(
x=l_border_norm, shape=border_ex_shape)
l_border_score = paddle.expand(x=l_score, shape=border_ex_shape)
l_border_mask = paddle.expand(x=l_mask, shape=border_ex_shape)
border_diff = l_border_split - f_border_split
abs_border_diff = paddle.abs(border_diff)
abs_border_diff = paddle.abs(border_diff)
border_sign = abs_border_diff < 1.0
border_sign = paddle.cast(border_sign, dtype='float32')
border_sign.stop_gradient = True
@ -72,15 +71,16 @@ class SASTLoss(nn.Layer):
(paddle.sum(l_border_score * l_border_mask) + 1e-5)
#tvo_loss
l_tvo_split, l_tvo_norm = paddle.split(l_tvo, num_or_sections=[8, 1], axis=1)
l_tvo_split, l_tvo_norm = paddle.split(
l_tvo, num_or_sections=[8, 1], axis=1)
f_tvo_split = f_tvo
tvo_ex_shape = l_tvo_norm.shape * np.array([1, 8, 1, 1])
l_tvo_norm_split = paddle.expand(x=l_tvo_norm, shape=tvo_ex_shape)
l_tvo_score = paddle.expand(x=l_score, shape=tvo_ex_shape)
l_tvo_mask = paddle.expand(x=l_mask, shape=tvo_ex_shape)
l_tvo_score = paddle.expand(x=l_score, shape=tvo_ex_shape)
l_tvo_mask = paddle.expand(x=l_mask, shape=tvo_ex_shape)
#
tvo_geo_diff = l_tvo_split - f_tvo_split
abs_tvo_geo_diff = paddle.abs(tvo_geo_diff)
abs_tvo_geo_diff = paddle.abs(tvo_geo_diff)
tvo_sign = abs_tvo_geo_diff < 1.0
tvo_sign = paddle.cast(tvo_sign, dtype='float32')
tvo_sign.stop_gradient = True
@ -91,15 +91,16 @@ class SASTLoss(nn.Layer):
(paddle.sum(l_tvo_score * l_tvo_mask) + 1e-5)
#tco_loss
l_tco_split, l_tco_norm = paddle.split(l_tco, num_or_sections=[2, 1], axis=1)
l_tco_split, l_tco_norm = paddle.split(
l_tco, num_or_sections=[2, 1], axis=1)
f_tco_split = f_tco
tco_ex_shape = l_tco_norm.shape * np.array([1, 2, 1, 1])
l_tco_norm_split = paddle.expand(x=l_tco_norm, shape=tco_ex_shape)
l_tco_score = paddle.expand(x=l_score, shape=tco_ex_shape)
l_tco_mask = paddle.expand(x=l_mask, shape=tco_ex_shape)
l_tco_score = paddle.expand(x=l_score, shape=tco_ex_shape)
l_tco_mask = paddle.expand(x=l_mask, shape=tco_ex_shape)
tco_geo_diff = l_tco_split - f_tco_split
abs_tco_geo_diff = paddle.abs(tco_geo_diff)
abs_tco_geo_diff = paddle.abs(tco_geo_diff)
tco_sign = abs_tco_geo_diff < 1.0
tco_sign = paddle.cast(tco_sign, dtype='float32')
tco_sign.stop_gradient = True
@ -109,13 +110,12 @@ class SASTLoss(nn.Layer):
tco_loss = paddle.sum(tco_out_loss * l_tco_score * l_tco_mask) / \
(paddle.sum(l_tco_score * l_tco_mask) + 1e-5)
# total loss
tvo_lw, tco_lw = 1.5, 1.5
score_lw, border_lw = 1.0, 1.0
total_loss = score_loss * score_lw + border_loss * border_lw + \
tvo_loss * tvo_lw + tco_loss * tco_lw
losses = {'loss':total_loss, "score_loss":score_loss,\
"border_loss":border_loss, 'tvo_loss':tvo_loss, 'tco_loss':tco_loss}
return losses
return losses

1
tools/infer/predict_cls.py
View File

@ -24,7 +24,6 @@ import numpy as np
import math
import time
import traceback
import paddle.fluid as fluid
import tools.infer.utility as utility
from ppocr.postprocess import build_post_process

1
tools/infer/predict_det.py
View File

@ -22,7 +22,6 @@ import cv2
import numpy as np
import time
import sys
import paddle
import tools.infer.utility as utility
from ppocr.utils.logging import get_logger

1
tools/infer/predict_rec.py
View File

@ -23,7 +23,6 @@ import numpy as np
import math
import time
import traceback
import paddle.fluid as fluid
import tools.infer.utility as utility
from ppocr.postprocess import build_post_process

2
tools/program.py
View File

@ -131,7 +131,7 @@ def check_gpu(use_gpu):
"model on CPU"
try:
if use_gpu and not paddle.fluid.is_compiled_with_cuda():
if use_gpu and not paddle.is_compiled_with_cuda():
print(err)
sys.exit(1)
except Exception as e: