def patText(s0):
'''make text pattern'''
arr = np.zeros((s0,s0), dtype=np.uint8)
s = int(round(s0/100.))
p1 = 0
pp1 = int(round(s0/10.))
for pos0 in np.linspace(0,s0,10):
cv2.putText(arr, 'helloworld', (p1,int(round(pos0))),
cv2.FONT_HERSHEY_COMPLEX_SMALL, fontScale=s,
color=255, thickness=s,
lineType=cv2.LINE_AA )
if p1:
p1 = 0
else:
p1 = pp1
return arr.astype(float)
python类FONT_HERSHEY_COMPLEX_SMALL的实例源码
def drawArrow(image, p, q, color, arrowMagnitude = 5, thickness=1, line_type=8, shift=0):
# Draw the principle line
cv2.line(image, tuple(p), tuple(q), color, thickness, line_type, shift);
# compute the angle alpha
angle = numpy.arctan2( p[1]-q[1], p[0]-q[0]);
# compute the coordinates of the first segment
p[0] = int(q[0] + arrowMagnitude * numpy.cos(angle + numpy.pi/4.0));
p[1] = int(q[1] + arrowMagnitude * numpy.sin(angle + numpy.pi/4.0));
# /Draw the first segment
cv2.line(image, tuple(p), tuple(q), color, thickness, line_type, shift);
# compute the coordinates of the second segment
p[0] = int(q[0] + arrowMagnitude * numpy.cos(angle - numpy.pi/4.0));
p[1] = int(q[1] + arrowMagnitude * numpy.sin(angle - numpy.pi/4.0));
# Draw the second segment
cv2.line(image, tuple(p), tuple(q), color, thickness, line_type, shift);
# cv2.putText(image, str(int(180.0*angle/numpy.pi)), tuple(p), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, 255 )
return image
def write_labels(video, label_dict, secs=1):
cap = cv2.VideoCapture(video)
w=int(cap.get(cv2.cv.CV_CAP_PROP_FRAME_WIDTH ))
h=int(cap.get(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT ))
out = cv2.VideoWriter('output.mp4', -1, 20.0, (w,h))
f_no = 0
fps = get_frame_rate(cap)
inc = int(fps * secs)
f_nos = label_dict.keys()
lbl = ''
while(cap.isOpened()):
ret, frame = cap.read()
if ret==True:
if f_no in f_nos:
try:
lbls = label_dict[f_no]
lbl = ",".join(lbls.keys())
except:
pass
cv2.putText(frame,lbl,(105, 105),cv2.FONT_HERSHEY_COMPLEX_SMALL,2,(0,0,255))
#out.write(frame)
cv2.imshow('frame',frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
else:
break
#inc
f_no += 1
cap.release()
out.release()
cv2.destroyAllWindows()
#if __name__ == '__main__' :
# get_frames_every_x_sec('video.mp4', '.')
def video():
global face_token
ft=cv2.freetype.createFreeType2()
ft.loadFontData(fontFileName='./data/font/simhei.ttf',id =0)
face_cascade = cv2.CascadeClassifier('./data/cascades/haarcascade_frontalface_alt.xml')
camera=cv2.VideoCapture(0)
count = 0
while(True):
ret,frame=camera.read()
gray=cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
faces=face_cascade.detectMultiScale(gray,1.3,5)
for(x,y,w,h) in faces:
img =cv2.rectangle(frame,(x,y),(x+w,y+h),(0,255,255),2)
if count%5<2:
f=cv2.resize(gray[y:y+h,x:x+w],(200,200))
cv2.imwrite('./data/temp/temp.pgm',f)
result=FaceAPI.searchItoI(image_file='./data/temp/temp.pgm')
if len(result)==4:
break
if result["results"][0]["confidence"] >= 80.00:
print result["results"][0]["confidence"]
face_token=result["results"][0]["face_token"]
detail=get_detail()
# shutil.copyfile("./data/temp/temp.pgm","./data/at/%s/%s.pgm"%(detail,time.strftime('%Y%m%d%H%M%S')))
print detail
ft.putText(img=img,text=detail[1], org=(x, y - 10), fontHeight=60,line_type=cv2.LINE_AA, color=(0,255,165), thickness=2, bottomLeftOrigin=True)
# count+=1
else:
print"Unknow face"
cv2.putText(img,"Unknow", (x, y - 10), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (0,0,225), 2)
count +=1
print count
cv2.namedWindow("image",cv2.WINDOW_NORMAL)
cv2.imshow("image",frame)
if cv2.waitKey(1000 / 12)&0xff==ord("q"):
break
camera.release()
cv2.destroyAllWindows()
def detect(filename):
global face_token
count=0
faces=[]
face_cascade = cv2.CascadeClassifier('./data/cascades/haarcascade_frontalface_alt.xml')
img = cv2.imread(filename)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces=face_cascade.detectMultiScale(gray, 1.3, 5)
ft=cv2.freetype.createFreeType2()
ft.loadFontData(fontFileName='./data/font/simhei.ttf',id =0)
for (x,y,w,h) in faces:
img = cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,255),3)
f = cv2.resize(gray[y:y+h, x:x+w], (200, 200))
cv2.imwrite('./data/search/{}/{}.pgm'.format(filesdir,count), f)
result=FaceAPI.searchItoI(image_file='./data/search/{}/{}.pgm'.format(filesdir,count))
if len(result)==4:
break
if result["results"][0]["confidence"] >= 80.00:
print result["results"][0]["confidence"]
face_token=result["results"][0]["face_token"]
print"face_token?{}".format(face_token)
detail=get_detail()
ft.putText(img=img,text=detail[1], org=(x, y - 10), fontHeight=30,line_type=cv2.LINE_AA, color=(0,255,165), thickness=1, bottomLeftOrigin=True)
else:
print"Unknow face"
cv2.putText(img,"Unknow", (x, y - 10), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (0,0,225), 2)
count+=1
cv2.imwrite(i,img)
def checkface_offline(filename):
face_cascade = cv2.CascadeClassifier('./data/cascades/haarcascade_frontalface_alt.xml')
img = cv2.imread(filename)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces=face_cascade.detectMultiScale(gray, 1.3, 5)
ft=cv2.freetype.createFreeType2()
ft.loadFontData(fontFileName='./data/font/simhei.ttf',id =0)
for (x,y,w,h) in faces:
img = cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,255),3)
f = cv2.resize(gray[y:y+h, x:x+w], (200, 200))
name=filelist+(str(random.randint(0,99)))
print name
cv2.imwrite('./img/face/{}.jpg'.format(name),f)
result=FaceAPI.searchItoI(image_file='./img/face/{}.jpg'.format(name))
confidence=result["results"][0]["confidence"]
if len(result)==3:
checkbody_n('./img/shutter/{}.jpg'.format(filelist))
if confidence >= 80.00:
face_token=result["results"][0]["face_token"]
detail=detailface(face_token)
cur.execute("insert into io_data values('%s',%s,'%s','%s','%s','%s','%s')"%(filelist,detail[0],detail[1],confidence,detail[2],face_token,fileLists))
conn.commit()
# checkbody_y('./img/shutter/{}.jpg'.format(filelist))
ft.putText(img=img,text=detail[1], org=(x, y - 10), fontHeight=30,line_type=cv2.LINE_AA, color=(0,255,165), thickness=1, bottomLeftOrigin=True)
else:
print"Unknow face"
face_token=result["results"][0]["face_token"]
detail=detailface(face_token)
random_ID=random.randint(100000000000,100000999999)
cv2.putText(img,"Unknow", (x, y - 10), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (0,0,225), 2)
cur.execute("insert into io_data values('%s',%s,'None','%s','%s','%s','%s')"%(filelist,random_ID,confidence,detail[2],face_token,fileLists))
conn.commit()
cv2.imwrite('./img/shutter/{}.jpg'.format(filelist),img)
def tile(cols, rows, imgs, titles=None):
font = cv2.FONT_HERSHEY_COMPLEX_SMALL
fontSize = 1
fontThickness = 2
pad=10
titleColor = (255,192,0)
hImg = imgs[0]
i = 0
z = None
row = []
for c in range(cols):
col = []
for r in range(rows):
if i<len(imgs):
img = imgs[i]
if titles is not None and i<len(titles):
img = img.copy()
size = cv2.getTextSize(titles[i], font, fontSize, fontThickness)[0]
cv2.putText(img, titles[i], (pad, size[1]+pad), font, fontSize, titleColor, thickness=fontThickness)
col.append(img)
else:
if z is None:
z = np.zeros_like(imgs[0])
col.append(z)
i+=1
row.append(np.concatenate(col, axis=0))
return np.concatenate(row, axis=1)
def checkface_online(filename):
i=0
img = cv2.imread(filename)
result_d=FaceAPI.detect(image_file=filename)
time.sleep(2)
if len(result_d)==3:
print result_d
if len(result_d)>3:
for i in range(0,len(result_d["faces"])):
face_token=result_d["faces"][i]["face_token"]
gender=result_d["faces"][i]["attributes"]["gender"]["value"]
age=result_d["faces"][i]["attributes"]["age"]["value"]
face_rectangle=result_d["faces"][i]["face_rectangle"]
x=face_rectangle["left"]
y=face_rectangle["top"]
w=face_rectangle["width"]
h=face_rectangle["height"]
img=cv2.rectangle(img,(x,y),(x+w,y+h),(0,225,225),2)
# cv2.imwrite('./img/shutter/{}.jpg'.format(filelist),img)
result_s=FaceAPI.searchTtoI(face_token=face_token)
time.sleep(1)
# print result_s
if len(result_s)==3:
print "result_s==3"
if i==0:
checkbody_n('./img/shutter/{}.jpg'.format(filelist))
if len(result_s)>3:
face_token=result_s["results"][0]["face_token"]
confidence=result_s["results"][0]["confidence"]
if confidence >= 80.00:
detail=detailface(face_token)
cur.execute("insert into io_data values('%s',%s,'%s','%s','%s','%s','%s')"%(filelist,detail[0],detail[1],confidence,gender,face_token,fileLists))
conn.commit()
ft=cv2.freetype.createFreeType2()
ft.loadFontData(fontFileName='./data/font/simhei.ttf',id =0)
ft.putText(img=img,text=detail[1], org=(x, y - 10), fontHeight=30,line_type=cv2.LINE_AA, color=(0,255,165), thickness=1, bottomLeftOrigin=True)
cv2.imwrite('./img/shutter/{}.jpg'.format(filelist),img)
if i==1:
checkbody_y('./img/shutter/{}.jpg'.format(filelist),face_token)
else:
print"Unknow face"
face_token=result_s["results"][0]["face_token"]
confidence=result_s["results"][0]["confidence"]
# random_ID=random.randint(100000000000,100000999999)
cv2.putText(img,"Unknow", (x, y - 10), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (0,0,225), 2)
cur.execute("insert into io_data values('%s','None','None','%s','%s','%s','%s')"%(filelist,confidence,gender,face_token,fileLists))
conn.commit()
cv2.imwrite('./img/shutter/{}.jpg'.format(filelist),img)
if i==1:
checkbody_n('./img/shutter/{}.jpg'.format(filelist))
i=i+1
def processRawImage(raw):
cv2.imshow("raw", raw)
mask = filterHue(raw)
#cv2.imshow("mask", mask)
#colorOnly = cv2.bitwise_and(raw, raw, mask = mask)
#cv2.imshow("colormasked", colorOnly)
#mask = cv2.threshold(mask, params["gray"], 255, 0)
result = raw.copy()
largestContour = findLargestContour(mask)
if largestContour is not None:
## M = cv2.moments(largestContour)
## if M["m00"] != 0:
## cx = int(M["m10"]/M["m00"])
## cy = int(M["m01"]/M["m00"])
## cv2.circle(result, (cx, cy), 8, (250, 250, 250), -1)
## hull = cv2.convexHull(largestContour)
## cv2.drawContours(result, [hull], 0, (0,255,0), 3)
x,y,w,h = cv2.boundingRect(largestContour)
center = (x+(w/2), y+(h/2))
cv2.rectangle(result, (x,y), (x+w,y+h), (40,0,120), 2)
cv2.circle(result, center, 8, (250, 250, 250), -1)
cv2.putText(result, str(center[0]-320), (x-50, y+15), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (255,0,0), 1)
cv2.putText(result, str(center[1]-240), (x-50, y+45), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (255,0,0), 1)
#perceivedFocalLength = distanceCalc.CalculatePerceivedFOVAtGivenDistance(w, targetSize[1]);
#params["FOV"] = int(perceivedFocalLength)
perceivedFocalLength = 652
calc = TriangleSimilarityDistanceCalculator(targetSize[0], perceivedFocalLength)
distance = calc.CalcualteDistance(w);
cv2.putText(result, str(distance) + " inches", (5, 23), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (255,0,0), 1)
## tPx = w
## distance = params["FOV"]/w
## cv2.putText(result, str(distance), (30, 30), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1, (0,0,0), 1)
#client.publish("5495.targetting", center[0]-320)
payload = { 'horizDelta': center[0] - 320, 'targetDistance': int(distance) }
client.publish(MQTT_TOPIC_TARGETTING, json.dumps(payload))
return result
def drawBoxes(img, boxes, categories, names, palette, scores=None, fade=False):
def clipCoord(xy):
return np.minimum(np.maximum(np.array(xy,dtype=np.int32),0),[img.shape[1]-1, img.shape[0]-1]).tolist()
cmap = palette.getMap(list=True)
font = cv2.FONT_HERSHEY_COMPLEX_SMALL
fontSize = 0.8
fontThickness = 1
pad=5
img=np.copy(img)
for box in range(boxes.shape[0]):
if fade and scores is not None:
iOrig = img
img=np.copy(img)
topleft = tuple(clipCoord(boxes[box][0:2]))
if categories is not None:
color = tuple(cmap[categories[box]])
else:
color = (0,0,255)
cv2.rectangle(img, topleft, tuple(clipCoord(boxes[box][2:5])), color, thickness=4)
if names:
title=names[box]
if scores is not None:
title+=": %.2f" % scores[box]
textpos=[topleft[0], topleft[1]-pad]
size = cv2.getTextSize(title, font, fontSize, fontThickness)[0]
boxTL = textpos[:]
boxTL[1] = boxTL[1] - size[1]
boxBR = list(topleft)
boxBR[0] = boxBR[0] + size[0]
cv2.rectangle(img, tuple(boxTL), tuple(boxBR), color, thickness=-1)
cv2.rectangle(img, tuple(boxTL), tuple(boxBR), color, thickness=4)
cv2.putText(img, title, tuple(textpos), font, fontSize, (255,255,255), thickness=fontThickness)
if fade and scores is not None:
img = scores[box] * img + (1.0-scores[box]) * iOrig
return img
