mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-06 00:57:33 +08:00
Modify yolov7 and visualize functions (#82)
modify yolov7 and visualize functions
This commit is contained in:
116
fastdeploy/vision/detection/scaled_yolov4.py
Normal file
116
fastdeploy/vision/detection/scaled_yolov4.py
Normal file
@@ -0,0 +1,116 @@
|
||||
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
from __future__ import absolute_import
|
||||
import logging
|
||||
from ... import FastDeployModel, Frontend
|
||||
from ... import c_lib_wrap as C
|
||||
|
||||
|
||||
class ScaledYOLOv4(FastDeployModel):
|
||||
def __init__(self,
|
||||
model_file,
|
||||
params_file="",
|
||||
runtime_option=None,
|
||||
model_format=Frontend.ONNX):
|
||||
# 调用基函数进行backend_option的初始化
|
||||
# 初始化后的option保存在self._runtime_option
|
||||
super(ScaledYOLOv4, self).__init__(runtime_option)
|
||||
|
||||
self._model = C.vision.detection.ScaledYOLOv4(
|
||||
model_file, params_file, self._runtime_option, model_format)
|
||||
# 通过self.initialized判断整个模型的初始化是否成功
|
||||
assert self.initialized, "ScaledYOLOv4 initialize failed."
|
||||
|
||||
def predict(self, input_image, conf_threshold=0.25, nms_iou_threshold=0.5):
|
||||
return self._model.predict(input_image, conf_threshold,
|
||||
nms_iou_threshold)
|
||||
|
||||
# 一些跟ScaledYOLOv4模型有关的属性封装
|
||||
# 多数是预处理相关,可通过修改如model.size = [1280, 1280]改变预处理时resize的大小(前提是模型支持)
|
||||
@property
|
||||
def size(self):
|
||||
return self._model.size
|
||||
|
||||
@property
|
||||
def padding_value(self):
|
||||
return self._model.padding_value
|
||||
|
||||
@property
|
||||
def is_no_pad(self):
|
||||
return self._model.is_no_pad
|
||||
|
||||
@property
|
||||
def is_mini_pad(self):
|
||||
return self._model.is_mini_pad
|
||||
|
||||
@property
|
||||
def is_scale_up(self):
|
||||
return self._model.is_scale_up
|
||||
|
||||
@property
|
||||
def stride(self):
|
||||
return self._model.stride
|
||||
|
||||
@property
|
||||
def max_wh(self):
|
||||
return self._model.max_wh
|
||||
|
||||
@size.setter
|
||||
def size(self, wh):
|
||||
assert isinstance(wh, [list, tuple]),\
|
||||
"The value to set `size` must be type of tuple or list."
|
||||
assert len(wh) == 2,\
|
||||
"The value to set `size` must contatins 2 elements means [width, height], but now it contains {} elements.".format(
|
||||
len(wh))
|
||||
self._model.size = wh
|
||||
|
||||
@padding_value.setter
|
||||
def padding_value(self, value):
|
||||
assert isinstance(
|
||||
value,
|
||||
list), "The value to set `padding_value` must be type of list."
|
||||
self._model.padding_value = value
|
||||
|
||||
@is_no_pad.setter
|
||||
def is_no_pad(self, value):
|
||||
assert isinstance(
|
||||
value, bool), "The value to set `is_no_pad` must be type of bool."
|
||||
self._model.is_no_pad = value
|
||||
|
||||
@is_mini_pad.setter
|
||||
def is_mini_pad(self, value):
|
||||
assert isinstance(
|
||||
value,
|
||||
bool), "The value to set `is_mini_pad` must be type of bool."
|
||||
self._model.is_mini_pad = value
|
||||
|
||||
@is_scale_up.setter
|
||||
def is_scale_up(self, value):
|
||||
assert isinstance(
|
||||
value,
|
||||
bool), "The value to set `is_scale_up` must be type of bool."
|
||||
self._model.is_scale_up = value
|
||||
|
||||
@stride.setter
|
||||
def stride(self, value):
|
||||
assert isinstance(
|
||||
value, int), "The value to set `stride` must be type of int."
|
||||
self._model.stride = value
|
||||
|
||||
@max_wh.setter
|
||||
def max_wh(self, value):
|
||||
assert isinstance(
|
||||
value, float), "The value to set `max_wh` must be type of float."
|
||||
self._model.max_wh = value
|
Reference in New Issue
Block a user