718c41634f
1.项目后端整体迁移至PaddleOCR-NCNN算法，已通过基本的兼容性测试 2.工程改为使用CMake组织，后续为了更好地兼容第三方库，不再提供QMake工程 3.重整权利声明文件，重整代码工程，确保最小化侵权风险 Log: 切换后端至PaddleOCR-NCNN，切换工程为CMake Change-Id: I4d5d2c5d37505a4a24b389b1a4c5d12f17bfa38c
122 lines
3.6 KiB
Python
122 lines
3.6 KiB
Python
# Tencent is pleased to support the open source community by making ncnn available.
|
|
#
|
|
# Copyright (C) 2020 THL A29 Limited, a Tencent company. All rights reserved.
|
|
#
|
|
# Licensed under the BSD 3-Clause License (the "License"); you may not use this file except
|
|
# in compliance with the License. You may obtain a copy of the License at
|
|
#
|
|
# https://opensource.org/licenses/BSD-3-Clause
|
|
#
|
|
# 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.
|
|
|
|
import sys
|
|
import cv2
|
|
import numpy as np
|
|
import ncnn
|
|
from ncnn.model_zoo import get_model
|
|
|
|
|
|
def draw_detection_objects_seg(image, class_names, objects, mat_map):
|
|
color = [128, 255, 128, 244, 35, 232]
|
|
color_count = len(color)
|
|
|
|
for obj in objects:
|
|
print(
|
|
"%d = %.5f at %.2f %.2f %.2f x %.2f\n"
|
|
% (obj.label, obj.prob, obj.rect.x, obj.rect.y, obj.rect.w, obj.rect.h)
|
|
)
|
|
|
|
cv2.rectangle(
|
|
image,
|
|
(int(obj.rect.x), int(obj.rect.y)),
|
|
(int(obj.rect.x + obj.rect.w), int(obj.rect.y + obj.rect.h)),
|
|
(255, 0, 0),
|
|
)
|
|
|
|
text = "%s %.1f%%" % (class_names[int(obj.label)], obj.prob * 100)
|
|
|
|
label_size, baseLine = cv2.getTextSize(text, cv2.FONT_HERSHEY_SIMPLEX, 0.5, 1)
|
|
|
|
x = obj.rect.x
|
|
y = obj.rect.y - label_size[1] - baseLine
|
|
if y < 0:
|
|
y = 0
|
|
if x + label_size[0] > image.shape[1]:
|
|
x = image.shape[1] - label_size[0]
|
|
|
|
cv2.rectangle(
|
|
image,
|
|
(int(x), int(y)),
|
|
(int(x + label_size[0]), int(y + label_size[1] + baseLine)),
|
|
(255, 255, 255),
|
|
-1,
|
|
)
|
|
|
|
cv2.putText(
|
|
image,
|
|
text,
|
|
(int(x), int(y + label_size[1])),
|
|
cv2.FONT_HERSHEY_SIMPLEX,
|
|
0.5,
|
|
(0, 0, 0),
|
|
)
|
|
|
|
width = mat_map.w
|
|
height = mat_map.h
|
|
size = mat_map.c
|
|
img_index2 = 0
|
|
threshold = 0.45
|
|
ptr2 = np.array(mat_map)
|
|
for i in range(height):
|
|
ptr1 = image[i].flatten()
|
|
img_index1 = 0
|
|
for j in range(width):
|
|
maxima = threshold
|
|
index = -1
|
|
for c in range(size):
|
|
# const float* ptr3 = ptr2 + c*width*height
|
|
ptr3 = ptr2[c].flatten()
|
|
if ptr3[img_index2] > maxima:
|
|
maxima = ptr3[img_index2]
|
|
index = c
|
|
|
|
if index > -1:
|
|
color_index = (index) * 3
|
|
if color_index < color_count:
|
|
b = color[color_index]
|
|
g = color[color_index + 1]
|
|
r = color[color_index + 2]
|
|
ptr1[img_index1] = b / 2 + ptr1[img_index1] / 2
|
|
ptr1[img_index1 + 1] = g / 2 + ptr1[img_index1 + 1] / 2
|
|
ptr1[img_index1 + 2] = r / 2 + ptr1[img_index1 + 2] / 2
|
|
|
|
img_index1 += 3
|
|
img_index2 += 1
|
|
|
|
image[i] = ptr1.reshape(image[i].shape)
|
|
|
|
cv2.imshow("image", image)
|
|
cv2.waitKey(0)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
if len(sys.argv) != 2:
|
|
print("Usage: %s [imagepath]\n" % (sys.argv[0]))
|
|
sys.exit(0)
|
|
|
|
imagepath = sys.argv[1]
|
|
|
|
m = cv2.imread(imagepath)
|
|
if m is None:
|
|
print("cv2.imread %s failed\n" % (imagepath))
|
|
sys.exit(0)
|
|
|
|
net = get_model("peleenet_ssd", num_threads=4, use_gpu=True)
|
|
|
|
objects, seg_out = net(m)
|
|
|
|
draw_detection_objects_seg(m, net.class_names, objects, seg_out)
|