未验证 提交 7cf31190 编写于 作者: W wangguanzhong 提交者: GitHub

add version check (#749)

* add version check

* update version check & python version for cornerpool
上级 9a2ae66d
......@@ -35,6 +35,7 @@
**注意:**
- 模型FPS在Tesla V100单卡环境中通过tools/eval.py进行测试
- CornerNet-Squeeze要求使用PaddlePaddle1.8及以上版本或适当的develop版本
- CornerNet-Squeeze中使用ResNet结构的骨干网络时,加入了FPN结构,骨干网络的输出feature map采用FPN中的P3层输出。
- \*CornerNet-Squeeze-dcn-mixup-cosine是基于原版CornerNet-Squeeze优化效果最好的模型,在ResNet的骨干网络基础上增加mixup预处理和使用cosine_decay
- FCOS使用GIoU loss、用location分支预测centerness、左上右下角点偏移量归一化和ground truth中心匹配策略
......
......@@ -8,7 +8,7 @@
## 简介
[YOLO v4](https://arxiv.org/abs/2004.10934)的Paddle实现版本
[YOLO v4](https://arxiv.org/abs/2004.10934)的Paddle实现版本,要求使用PaddlePaddle2.0.0及以上版本或适当的develop版本
目前转换了[darknet](https://github.com/AlexeyAB/darknet)中YOLO v4的权重,可以直接对图片进行预测,在[test-dev2019](http://cocodataset.org/#detection-2019)中精度为43.5%。另外,支持VOC数据集上finetune,精度达到85.5%
......@@ -19,6 +19,7 @@
- SPP模块
- ciou loss
- label_smooth
- grid_sensitive
## 模型库
下表中展示了当前支持的网络结构。
......@@ -39,7 +40,7 @@
1. mish激活函数优化
2. mosaic数据预处理实现
3. scale\_x\_y为yolo_box中decode时对box的位置进行微调,该功能将在Paddle2.0版本中实现
## 如何贡献代码
......
import os
import paddle.fluid as fluid
use_cpp = False
file_dir = os.path.dirname(os.path.abspath(__file__))
fluid.load_op_library(os.path.join(file_dir, 'src/cornerpool_lib.so'))
try:
fluid.load_op_library(os.path.join(file_dir, 'src/cornerpool_lib.so'))
use_cpp = True
except:
print(
'Warning: cornerpool_lib.so not found, use python version instead which may drop the inference speed. Compile in ppdet/ext_op at first if you need cpp version.'
)
from paddle.fluid.layer_helper import LayerHelper
......@@ -14,6 +22,19 @@ __all__ = [
]
def cornerpool_op(layer_type, input, name):
helper = LayerHelper(layer_type, input=input, name=name)
dtype = helper.input_dtype()
output = helper.create_variable_for_type_inference(dtype)
max_map = helper.create_variable_for_type_inference(dtype)
helper.append_op(
type=layer_type,
inputs={"X": input},
outputs={"Output": output,
"MaxMap": max_map})
return output
def bottom_pool(input, is_test=False, name=None):
"""
This layer calculates the bottom pooling output based on the input.
......@@ -34,16 +55,28 @@ def bottom_pool(input, is_test=False, name=None):
output = corner_pool.bottom_pool(input)
"""
if is_test:
helper = LayerHelper('bottom_pool', **locals())
dtype = helper.input_dtype()
output = helper.create_variable_for_type_inference(dtype)
max_map = helper.create_variable_for_type_inference(dtype)
helper.append_op(
type="bottom_pool",
inputs={"X": input},
outputs={"Output": output,
"MaxMap": max_map})
return output
if use_cpp:
output = cornerpool_op("bottom_pool", input, name)
return output
def cond(i, output):
return i < H
def body(i, output):
cur = fluid.layers.slice(output, [2], [i], [H])
next = fluid.layers.slice(output, [2], [0], [H - i])
max_v = fluid.layers.elementwise_max(cur, next)
orig = fluid.layers.slice(output, [2], [0], [i])
output = fluid.layers.concat([orig, max_v], axis=2)
i = i * 2
return [i, output]
H = fluid.layers.shape(input)[2]
i = fluid.layers.fill_constant(shape=[1], dtype='int32', value=1)
output = input
output = fluid.layers.while_loop(cond, body, [i, output])
return output[-1]
H = input.shape[2]
i = 1
output = input
......@@ -77,16 +110,27 @@ def top_pool(input, is_test=False, name=None):
output = corner_pool.top_pool(input)
"""
if is_test:
helper = LayerHelper('top_pool', **locals())
dtype = helper.input_dtype()
output = helper.create_variable_for_type_inference(dtype)
max_map = helper.create_variable_for_type_inference(dtype)
helper.append_op(
type="top_pool",
inputs={"X": input},
outputs={"Output": output,
"MaxMap": max_map})
return output
if use_cpp:
output = cornerpool_op("top_pool", input, name)
return output
def cond(i, output):
return i < H
def body(i, output):
cur = fluid.layers.slice(output, [2], [0], [H - i])
next = fluid.layers.slice(output, [2], [i], [H])
max_v = fluid.layers.elementwise_max(cur, next)
orig = fluid.layers.slice(output, [2], [H - i], [H])
output = fluid.layers.concat([max_v, orig], axis=2)
i = i * 2
return [i, output]
H = fluid.layers.shape(input)[2]
i = fluid.layers.fill_constant(shape=[1], dtype='int32', value=1)
output = input
output = fluid.layers.while_loop(cond, body, [i, output])
return output[-1]
H = input.shape[2]
i = 1
......@@ -121,16 +165,27 @@ def right_pool(input, is_test=False, name=None):
output = corner_pool.right_pool(input)
"""
if is_test:
helper = LayerHelper('right_pool', **locals())
dtype = helper.input_dtype()
output = helper.create_variable_for_type_inference(dtype)
max_map = helper.create_variable_for_type_inference(dtype)
helper.append_op(
type="right_pool",
inputs={"X": input},
outputs={"Output": output,
"MaxMap": max_map})
return output
if use_cpp:
output = cornerpool_op("right_pool", input, name)
return output
def cond(i, output):
return i < W
def body(i, output):
cur = fluid.layers.slice(output, [3], [i], [W])
next = fluid.layers.slice(output, [3], [0], [W - i])
max_v = fluid.layers.elementwise_max(cur, next)
orig = fluid.layers.slice(output, [3], [0], [i])
output = fluid.layers.concat([orig, max_v], axis=-1)
i = i * 2
return [i, output]
W = fluid.layers.shape(input)[3]
i = fluid.layers.fill_constant(shape=[1], dtype='int32', value=1)
output = input
output = fluid.layers.while_loop(cond, body, [i, output])
return output[-1]
W = input.shape[3]
i = 1
......@@ -165,16 +220,27 @@ def left_pool(input, is_test=False, name=None):
output = corner_pool.left_pool(input)
"""
if is_test:
helper = LayerHelper('left_pool', **locals())
dtype = helper.input_dtype()
output = helper.create_variable_for_type_inference(dtype)
max_map = helper.create_variable_for_type_inference(dtype)
helper.append_op(
type="left_pool",
inputs={"X": input},
outputs={"Output": output,
"MaxMap": max_map})
return output
if use_cpp:
output = cornerpool_op("left_pool", input, name)
return output
def cond(i, output):
return i < W
def body(i, output):
cur = fluid.layers.slice(output, [3], [0], [W - i])
next = fluid.layers.slice(output, [3], [i], [W])
max_v = fluid.layers.elementwise_max(cur, next)
orig = fluid.layers.slice(output, [3], [W - i], [W])
output = fluid.layers.concat([max_v, orig], axis=-1)
i = i * 2
return [i, output]
W = fluid.layers.shape(input)[3]
i = fluid.layers.fill_constant(shape=[1], dtype='int32', value=1)
output = input
output = fluid.layers.while_loop(cond, body, [i, output])
return output[-1]
W = input.shape[3]
i = 1
......
......@@ -29,6 +29,7 @@ try:
from collections.abc import Sequence
except Exception:
from collections import Sequence
from ppdet.utils.check import check_version
__all__ = ['YOLOv3Head', 'YOLOv4Head']
......@@ -70,6 +71,7 @@ class YOLOv3Head(object):
downsample=[32, 16, 8],
scale_x_y=1.0,
clip_bbox=True):
check_version('2.0.0')
self.norm_decay = norm_decay
self.num_classes = num_classes
self.anchor_masks = anchor_masks
......
......@@ -22,6 +22,7 @@ from paddle import fluid
from ppdet.core.workspace import register
import numpy as np
from ppdet.utils.check import check_version
__all__ = ['CornerNetSqueeze']
......@@ -48,6 +49,7 @@ class CornerNetSqueeze(object):
corner_head='CornerHead',
num_classes=80,
fpn=None):
check_version('1.8.0')
super(CornerNetSqueeze, self).__init__()
self.backbone = backbone
self.corner_head = corner_head
......
......@@ -86,6 +86,7 @@ class YOLOv3Loss(object):
use_label_smooth=self._label_smooth,
scale_x_y=scale_x_y,
name=prefix_name + "yolo_loss" + str(i))
losses.append(fluid.layers.reduce_mean(loss))
return {'loss': sum(losses)}
......
......@@ -21,6 +21,8 @@ import sys
import paddle.fluid as fluid
import logging
import six
import paddle.version as fluid_version
logger = logging.getLogger(__name__)
__all__ = ['check_gpu', 'check_version', 'check_config']
......@@ -45,20 +47,27 @@ def check_gpu(use_gpu):
pass
def check_version():
def check_version(version='1.7.0'):
"""
Log error and exit when the installed version of paddlepaddle is
not satisfied.
"""
err = "PaddlePaddle version 1.6 or higher is required, " \
err = "PaddlePaddle version {} or higher is required, " \
"or a suitable develop version is satisfied as well. \n" \
"Please make sure the version is good with your code." \
try:
fluid.require_version('1.7.0')
except Exception as e:
logger.error(err)
sys.exit(1)
"Please make sure the version is good with your code.".format(version)
version_installed = [
fluid_version.major, fluid_version.minor, fluid_version.patch,
fluid_version.rc
]
if version_installed == ['0', '0', '0', '0']:
return
version_split = version.split('.')
length = min(len(version_installed), len(version_split))
for i in six.moves.range(length):
if version_installed[i] < version_split[i]:
raise Exception(err)
def check_config(cfg):
......
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