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yolov8.py
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yolov8.py
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from ultralytics import YOLO
import cv2
import time
import numpy as np
import sys
import similarity
import os
from keras.utils import image_utils as image
from keras.applications.imagenet_utils import preprocess_input
import numpy as np
import cv2
from image_similarity import *
from skimage.metrics import structural_similarity as compare_ssim
# 计算旋转变换矩阵
def handle_rotate_val(x, y, rotate):
cos_val = np.cos(np.deg2rad(rotate))
sin_val = np.sin(np.deg2rad(rotate))
return np.float32([
[cos_val, sin_val, x * (1 - cos_val) - y * sin_val],
[-sin_val, cos_val, x * sin_val + y * (1 - cos_val)]
])
def zhengqiang2(img):
img_t = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
h, s, v = cv2.split(img_t)
v2 = np.clip(cv2.add(2 * v, 20), 0, 255)
img2 = np.uint8(cv2.merge((h, s, v2)))
img2 = cv2.cvtColor(img2, cv2.COLOR_HSV2BGR)
return img2
# 图像旋转（以任意点为中心旋转）
def image_rotate(src, rotate=0):
h, w, c = src.shape
M = handle_rotate_val(w // 2, h // 2, rotate)
img = cv2.warpAffine(src, M, (w, h))
return img
def yuxianpinggu(x, y):
ans = 0
for i in range(0, 3):
ans = ans + (x[i] - y[i])**2
return ans
def zengqiangduibi(img0):
a = 2
b = 0.8
dst = img0
for i in range(img0.shape[0]):
for j in range(img0.shape[1]):
for c in range(3):
color = img0[i, j][c] * a + b
if color > 255:
dst[i, j][c] = 255
elif color < 0:
dst[i, j][c] = 0
return dst
def zengqiangduibi1(img0):
clahe = cv2.createCLAHE(clipLimit=10, tileGridSize=(20, 20))
# convert from BGR to LAB color space
lab = cv2.cvtColor(img0, cv2.COLOR_BGR2LAB)
l, a, b = cv2.split(lab) # split on 3 different channels
l2 = clahe.apply(l) # apply CLAHE to the L-channel
lab = cv2.merge((l2, a, b)) # merge channels
img0 = cv2.cvtColor(lab, cv2.COLOR_LAB2BGR) # convert from LAB to BGR
return img0
class getbqujieguo():
def __init__(self, images):
# Load a model
# load an official model
model = YOLO("/home/zzb/ultralytics/weights/cqu.pt")
# Predict with the model
# img0=cv2.imread(file_pathname+filename)
img0 = images
# img0=zhengqiang2(img0)
img0 = zengqiangduibi1(img0)
# img0=log_transfor(img0,-100)
time.sleep(0.1)
res = model(images, conf=0.55, iou=0.2) # predict on an image
res = list(res)[0] # get result from generator
up = []
down = []
for i in res.boxes.numpy():
# print(i.xyxy[0].tolist())
if i.xyxy[0][3] > 350:
down.append(i.xyxy[0])
else:
up.append(i.xyxy[0])
res_plotted = res.plot()
# self.plot_image= res_plotted
upjieguo = []
simjieguo = []
self.fabujieguo = ''
up.sort(key=lambda x: x[0])
if len(up) == 3:
juhe = []
for i in range(3):
tmp0 = img0[int(up[i][1]):int(up[i][3]),
int(up[i][0]):int(up[i][2])]
# cv2.imwrite("/home/zzb/test1/" + filename[0:len(filename) - 4] + str(i) + str(1) + ".jpg", tmp0)
tmp1 = cv2.mean(tmp0)
juhe.append(tmp1)
for i in range(2, -1, -1):
tmp0 = img0[int(up[i][1]):int(up[i][3]),
int(up[i][0]):int(up[i][2])]
tmp1 = img0[int(up[i - 1][1]):int(up[i - 1][3]),
int(up[i - 1][0]):int(up[i - 1][2])]
tmp0 = cv2.resize(tmp0, (224, 224),
interpolation=cv2.INTER_LINEAR)
tmp1 = cv2.resize(tmp1, (224, 224),
interpolation=cv2.INTER_LINEAR)
jieguo = similarity.runAllImageSimilaryFun(tmp0, tmp1)
xiangsidu = yuxianpinggu(juhe[i], juhe[i - 1])
tmp2 = np.hstack((tmp0, tmp1))
if i == 0:
upjieguo.append(min(jieguo))
else:
upjieguo.append(min(jieguo))
simjieguo.append(xiangsidu)
print(juhe)
print(simjieguo)
print(upjieguo)
# jieguozong=[]
# jieguozong.append(simjieguo,upjieguo,[0,2,1])
print("sim ssssss up:", max(simjieguo) - min(simjieguo))
zidian = {0: 0, 1: 2, 2: 1}
if max(simjieguo) - min(simjieguo) > 650 and max(upjieguo) - min(upjieguo) > 0.05:
print("666")
for i in range(2, -1, -1):
tmp0 = img0[int(up[i][1]):int(up[i][3]),
int(up[i][0]):int(up[i][2])]
tmp1 = img0[int(up[i - 1][1]):int(up[i - 1][3]),
int(up[i - 1][0]):int(up[i - 1][2])]
tmp0 = cv2.resize(tmp0, (224, 224),
interpolation=cv2.INTER_AREA)
tmp1 = cv2.resize(tmp1, (224, 224),
interpolation=cv2.INTER_AREA)
tmp2 = np.hstack((tmp0, tmp1))
if min(simjieguo) == simjieguo[2 - i]:
k = zidian[2 - i]
print("shangcengcuod shi" + str(k) + "ge")
self.fabujieguo = str(k) + "/"
# cv2.rectangle(img0,(500,100),(1000,500),(0,255,0),3)
cv2.rectangle(img0, (int(up[k][0]), int(up[k][1])),
(int(up[k][2]), int(up[k][3])), (0, 255, 0), 2)
# cv2.imwrite("/home/zzb/xiangsi/"+filename[0:len(filename)-4]+str(i)+str(1)+".jpg",tmp2)
else:
pass
# cv2.imwrite("/home/zzb/dif/"+filename[0:len(filename)-4]+str(i)+str(1)+".jpg",tmp2)
else:
print("yiyang")
# cv2.imwrite("/home/zzb/xiangsi/" + filename[0:len(filename) - 4] + str(i) + str(1) + ".jpg", img0)
downjieguo = []
simjieguo = []
down.sort(key=lambda x: x[0])
if len(down) == 3:
juhe = []
for i in range(3):
tmp0 = img0[int(down[i][1]):int(down[i][3]),
int(down[i][0]):int(down[i][2])]
tmp1 = cv2.mean(tmp0)
juhe.append(tmp1)
for i in range(2, -1, -1):
tmp0 = img0[int(down[i][1]):int(down[i][3]),
int(down[i][0]):int(down[i][2])]
tmp1 = img0[int(down[i - 1][1]):int(down[i - 1][3]),
int(down[i - 1][0]):int(down[i - 1][2])]
tmp0 = cv2.resize(tmp0, (224, 224),
interpolation=cv2.INTER_LINEAR)
tmp1 = cv2.resize(tmp1, (224, 224),
interpolation=cv2.INTER_LINEAR)
jieguo = similarity.runAllImageSimilaryFun(tmp0, tmp1)
xiangsidu = yuxianpinggu(juhe[i], juhe[i - 1])
tmp2 = np.hstack((tmp0, tmp1))
if i == 0:
downjieguo.append(min(jieguo))
else:
downjieguo.append(min(jieguo))
simjieguo.append(xiangsidu)
print(juhe)
print(simjieguo)
print(upjieguo)
# jieguozong=[]
# jieguozong.append(simjieguo,upjieguo,[0,2,1])
zidian = {0: 0, 1: 2, 2: 1}
print("sim ssssss:", max(simjieguo) - min(simjieguo))
if max(simjieguo) - min(simjieguo) > 650 and max(downjieguo) - min(downjieguo) > 0.05:
print("666")
for i in range(2, -1, -1):
tmp0 = img0[int(down[i][1]):int(down[i][3]),
int(down[i][0]):int(down[i][2])]
tmp1 = img0[int(down[i - 1][1]):int(down[i - 1][3]),
int(down[i - 1][0]):int(down[i - 1][2])]
tmp0 = cv2.resize(tmp0, (224, 224),
interpolation=cv2.INTER_AREA)
tmp1 = cv2.resize(tmp1, (224, 224),
interpolation=cv2.INTER_AREA)
tmp2 = np.hstack((tmp0, tmp1))
if min(simjieguo) == simjieguo[2 - i]:
k = zidian[2 - i]
print("xiacengcuod shi" + str(k) + "ge")
if self.fabujieguo == '':
self.fabujieguo = "/"+self.fabujieguo
self.fabujieguo = self.fabujieguo + str(k)
# cv2.rectangle(img0,(500,100),(1000,500),(0,255,0),3)
cv2.rectangle(img0, (int(down[k][0]), int(down[k][1])),
(int(down[k][2]), int(down[k][3])), (0, 255, 0), 2)
# cv2.imwrite("/home/zzb/xiangsi/"+filename[0:len(filename)-4]+str(i)+str(1)+".jpg",tmp2)
else:
pass
# cv2.imwrite("/home/zzb/dif/"+filename[0:len(filename)-4]+str(i)+str(1)+".jpg",tmp2)
else:
print("yiyang")
# cv2.imwrite("/home/zzb/xiangsi/"+filename[0:len(filename)-4]+str(i)+str(1)+".jpg",img0)
self.plot_image = img0
self.det_image = res_plotted
def get_jieguo(self):
return self.fabujieguo
def get_plot_image(self):
return self.plot_image
def get_det_image(self):
return self.det_image