def count_1():
# cap = cv2.VideoCapture('http://192.168.1.104:8080/shot.jpg')
型号 = v4.get()
reta = os.path.isfile(r"./imgs/" + 型号 + 'temp.jpg')
if not reta:
a = showinfo(title="样本确认", message="没有样本，请先登录！")
cv2.destroyAllWindows()
return()
img1 = cv2.imread(r"./imgs/" + 型号 + 'temp.jpg',0)
config = {'host':'127.0.0.1',
'user':'******',
'password':'******',
'port':'3306',
'database':'test',
'charset':'utf8'
}
try:
conn = mysql.connector.Connect(**config)
except mysql.connector.Error as e:
print('connect fails!{}'.format(e))
cursor = conn.cursor()
#查
try:
sql = "SELECT * FROM prov WHERE XH = %s"
cursor.execute(sql,(型号,))
sel_data = cursor.fetchone()
print(sel_data)
except mysql.connector.Error as e:
print('query error!{}'.format(e))
finally:
cursor.close()
conn.close()
cv2.namedWindow("image")
try:
w,h,threshold = sel_data[1],sel_data[2],sel_data[3]
except:
w = img1.shape[1]
h = img1.shape[0]
threshold = 69#0.78#0.80 #0.63
if w < img1.shape[1] or h < img1.shape[0]:
w = img1.shape[1]
h = img1.shape[0]
threshold = 69#0.78#0.80 #0.63
cv2.createTrackbar('w','image',w,255,nothing)
cv2.createTrackbar('h','image',h,255,nothing)
cv2.createTrackbar('threshold','image',threshold,100,nothing)
cap = cv2.VideoCapture(0)
i=0
while(1):
ret,image1 = cap.read()
i += 1
if i == 20:
break
cap.release()
while(1):
w = cv2.getTrackbarPos('w','image')
h = cv2.getTrackbarPos('h','image')
threshold = cv2.getTrackbarPos('threshold','image')/100
if img1.shape[1] > 1.1*w or img1.shape[0] > 1.1*h:
a = showinfo(title="w|h确认", message="w|h数值过小，请再试一次！")
cv2.destroyAllWindows()
break
img = cv2.resize(image1,(800,600),interpolation = cv2.INTER_CUBIC)
rectangles = []
counter = 1
scaleFactor =2#1.25
scale = 1
font = cv2.FONT_HERSHEY_PLAIN
#寻找roi轮廓并作形状比较，<0.1 填充矩形
for resized in pyramid(img,scaleFactor):
scale = float(img.shape[1]) / float(resized.shape[1])
for (x,y,roi) in sliding_window(resized,20,(w,h)):
if roi.shape[1] != w or roi.shape[0] != h:
#print("here")
continue
try:
img2 = cv2.cvtColor(roi,cv2.COLOR_BGR2GRAY)
ret = cv2.matchTemplate(img2,img1,cv2.TM_CCOEFF_NORMED)
# 3.这边是Python/Numpy的知识，后面解释
loc = np.where(ret >= threshold) # 匹配程度大于%80的坐标y,x
for pt in zip(*loc[::-1]): # *号表示可选参数
rx,ry,rx2,ry2 = int(x*scale),int(y*scale),int((x+w)*scale),int((y+h)*scale)
rectangles.append([rx,ry,rx2,ry2,(ret[pt[0],pt[1]])])
except:
pass
counter += 1
windows = np.array(rectangles)
boxes = nms(windows,1)
if len(boxes) > 0:
a = boxes.tolist()
c = []
for i in a:
if i not in c:
c.append(i)
a = c
else:
a = []
for (x,y,x2,y2,score) in a:
cv2.rectangle(img,(int(x),int(y)),(int(x2),int(y2)),(0,0,255),1)
cv2.putText(img,"%f"%score,(int(x),int(y)),font,1,(0,0,255))
v2.set(len(a))
cv2.imshow("image",img)
q = cv2.waitKey(50) & 0xff
if q == 13: # Enter
#name = v5.get()+v4.get()+'.jpg'
cv2.imwrite("./dinDan/temp.jpg",img)
config = {'host':'127.0.0.1',
'user':'******',
'password':'******',
'port':'3306',
'database':'test',
'charset':'utf8'
}
型号 = v4.get()
try:
conn = mysql.connector.Connect(**config)
except mysql.connector.Error as e:
print('connect fails!{}'.format(e))
cursor = conn.cursor()
#改
try:
sql = "Update prov Set XH = %s , w = %s ,h = %s ,threshold = %s Where XH = %s"
cursor.execute(sql,(型号,w,h,int(threshold*100),型号))
except mysql.connector.Error as e:
print('Update error!{}'.format(e))
finally:
conn.commit()
cursor.close()
conn.close()
break
cv2.destroyAllWindows()
def count_1():
#global ret
# cap = cv2.VideoCapture('http://192.168.1.104:8080/shot.jpg')
型号 = v4.get()
reta = os.path.isfile(r"./imgs/" + 型号 + 'temp.jpg')
if not reta:
a = showinfo(title="样本确认", message="没有样本，请先登录！")
cv2.destroyAllWindows()
return ()
img1 = cv2.imread(r"./imgs/" + 型号 + 'temp.jpg', 0)
pathfile = r'dataBase/test.mdb'
tablename = r'prov'
conn = mdb_conn(pathfile)
cur = conn.cursor()
#查
sql = "SELECT * FROM " + tablename + " where 型号 = '" + 型号 + "'"
sel_data = mdb_sel(cur, sql)
cv2.namedWindow("image")
try:
w, h, threshold = sel_data[0][1], sel_data[0][2], sel_data[0][3]
except:
w = img1.shape[1]
h = img1.shape[0]
threshold = 69 #0.78#0.80 #0.63
if w < img1.shape[1] or h < img1.shape[0]:
w = img1.shape[1]
h = img1.shape[0]
threshold = 69 #0.78#0.80 #0.63
cv2.createTrackbar('w', 'image', w, 255, nothing)
cv2.createTrackbar('h', 'image', h, 255, nothing)
cv2.createTrackbar('threshold', 'image', threshold, 100, nothing)
cap = cv2.VideoCapture(1)
i = 0
while (1):
ret, image1 = cap.read()
i += 1
if i == 10:
break
cap.release()
while (1):
w = cv2.getTrackbarPos('w', 'image')
h = cv2.getTrackbarPos('h', 'image')
threshold = cv2.getTrackbarPos('threshold', 'image') / 100
if img1.shape[1] > 1.1 * w or img1.shape[0] > 1.1 * h:
a = showinfo(title="w|h确认", message="w|h数值过小，请再试一次！")
cv2.destroyAllWindows()
break
img = cv2.resize(image1, (800, 600), interpolation=cv2.INTER_CUBIC)
rectangles = []
counter = 1
scaleFactor = 2 #1.25
scale = 1
font = cv2.FONT_HERSHEY_PLAIN
#寻找roi轮廓并作形状比较，<0.1 填充矩形
for resized in pyramid(img, scaleFactor):
scale = float(img.shape[1]) / float(resized.shape[1])
for (x, y, roi) in sliding_window(resized, 20, (w, h)):
if roi.shape[1] != w or roi.shape[0] != h:
#print("here")
continue
try:
img2 = cv2.cvtColor(roi, cv2.COLOR_BGR2GRAY)
ret = cv2.matchTemplate(img2, img1, cv2.TM_CCOEFF_NORMED)
# 3.这边是Python/Numpy的知识，后面解释
loc = np.where(ret >= threshold) # 匹配程度大于%80的坐标y,x
for pt in zip(*loc[::-1]): # *号表示可选参数
rx, ry, rx2, ry2 = int(x * scale), int(y * scale), int(
(x + w) * scale), int((y + h) * scale)
rectangles.append(
[rx, ry, rx2, ry2, (ret[pt[0], pt[1]])])
except:
pass
counter += 1
windows = np.array(rectangles)
boxes = nms(windows, 1)
if len(boxes) > 0:
a = boxes.tolist()
c = []
for i in a:
if i not in c:
c.append(i)
a = c
else:
a = []
for (x, y, x2, y2, score) in a:
cv2.rectangle(img, (int(x), int(y)), (int(x2), int(y2)),
(0, 0, 255), 1)
cv2.putText(img, "%f" % score, (int(x), int(y)), font, 1,
(0, 0, 255))
v2.set(len(a))
cv2.imshow("image", img)
q = cv2.waitKey(50) & 0xff
if q == 13: # Enter
#增
sql = "Insert Into " + tablename + " Values ('" + 型号 + "', " + str(
w) + ", " + str(h) + ", " + str(threshold * 100) + ")"
print(sql)
if mdb_add(conn, cur, sql):
print("插入成功！")
else:
print("插入失败！")
#改
sql = "Update " + tablename + " Set 型号 = '" + 型号 + "', w = " + str(
w) + ", threshold = " + str(
threshold *
100) + ", h = " + str(h) + " where 型号 = '" + 型号 + "'"
if mdb_modi(conn, cur, sql):
print("修改成功！")
else:
print("修改失败！")
cur.close() #关闭游标
conn.close() #关闭数据库连接
break
cv2.destroyAllWindows()
while(1):
w = cv2.getTrackbarPos('w','image')
h = cv2.getTrackbarPos('h','image')
#w,h = img1.shape[:2]
img = cv2.imread(test_image)
rectangles = []
counter = 1
scaleFactor =2#1.25
scale = 1
font = cv2.FONT_HERSHEY_PLAIN
#寻找roi轮廓并作形状比较，<0.1 填充矩形
for resized in pyramid(img,scaleFactor):
scale = float(img.shape[1]) / float(resized.shape[1])
for (x,y,roi) in sliding_window(resized,20,(w,h)):
if roi.shape[1] != w or roi.shape[0] != h:
continue
try:
'''
'''
img2 = cv2.cvtColor(roi,cv2.COLOR_BGR2GRAY)
ret = cv2.matchTemplate(img2,img1,cv2.TM_CCOEFF_NORMED)
'''
for score1 in ret:
for score in score1:
print(score)
img_path = "/home/dvaliu/Downloads/CarData/TestImages/test-10.pgm"
svm, extractor = car_detector()
detect = cv2.xfeatures2d.SIFT_create()
w, h = 100, 40
img = cv2.imread(img_path)
#img = cv2.imread(test_image)
rectangles = []
counter = 1
scaleFactor = 1.25
scale = 1
font = cv2.FONT_HERSHEY_PLAIN
for resized in pyramid(img, scaleFactor):
scale = float(img.shape[1]) / float(resized.shape[1])
for (x, y, roi) in sliding_window(resized, 20, (100, 40)):
if roi.shape[1] != w or roi.shape[0] != h:
continue
try:
bf = bow_features(roi, extractor, detect)
_, result = svm.predict(bf)
a, res = svm.predict(bf, flags=cv2.ml.STAT_MODEL_RAW_OUTPUT | cv2.ml.STAT_MODEL_UPDATE_MODEL)
print "Class: %d, Score: %f, a: %s" % (result[0][0], res[0][0], res)
score = res[0][0]
if result[0][0] == 1:
if score < -1.0:
rx, ry, rx2, ry2 = int(x * scale), int(y * scale), int((x+w) * scale), int((y+h) * scale)
rectangles.append([rx, ry, rx2, ry2, abs(score)])