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119 lines
2.9 KiB
119 lines
2.9 KiB
import cv2
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import numpy as np
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import json
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from matplotlib import pyplot as plt
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import cv2
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import numpy as np
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import json
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import os
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from matplotlib import pyplot as plt
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import xml.etree.ElementTree as ET
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import cv2
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import numpy as np
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import os
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import json
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from pysolar.solar import *
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from datetime import datetime
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def calcAvg(img,locations_xml):
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locations_extracted = []
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loc_images = {}
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average_values = {}
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for i in range( len( locations_xml ) ):
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try:
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locations_extracted.append([])
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for j in range(4):
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locations_extracted[i].append(locations_xml[i][1][j].attrib)
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locations_extracted[i].append(locations_xml[i].attrib['occupied'])
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locations_extracted[i].append(locations_xml[i].attrib['id'])
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except Exception:
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print("xml corrupt!")
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return {}
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for col in range(len(img)):
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for pix in range(len(img[col])):
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if (img[col][pix] == [255,255,255]).all():
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img[col][pix] == [255,255,254]
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for i in range(len(locations_extracted)):
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temp = locations_extracted[i]
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pts = np.array([[int(temp[0]['x']),int(temp[0]['y'])],
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[int(temp[1]['x']),int(temp[1]['y'])],
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[int(temp[2]['x']),int(temp[2]['y'])],
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[int(temp[3]['x']),int(temp[3]['y'])]])
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rect = cv2.boundingRect(pts)
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x,y,w,h = rect
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croped = img[y:y+h, x:x+w].copy()
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pts = pts - pts.min(axis=0)
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mask = np.zeros(croped.shape[:2], np.uint8)
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cv2.drawContours(mask, [pts], -1, (255, 255, 255), -1, cv2.LINE_AA)
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dst = cv2.bitwise_and(croped, croped, mask=mask)
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bg = np.ones_like(croped, np.uint8)*255
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cv2.bitwise_not(bg,bg, mask=mask)
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dst2 = bg+ dst
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blurred = cv2.GaussianBlur(dst2,(5,5),3)
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edges = cv2.Canny(blurred,100,100)
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if not temp[4] in loc_images:
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loc_images[temp[4]] = {}
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loc_images[temp[4]][temp[5]] = edges
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for state in loc_images:
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average_values[state] = {}
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for lot in loc_images[state]:
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reps = 0
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for col in loc_images[state][lot]:
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for pix in col:
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if(pix == 255):
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reps += 1
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average_values[state][lot] = reps
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print (average_values)
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return average_values
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def generateAvg():
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dates = os.listdir('./PKLot/PKLot/PUCPR/Sunny')
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imgs = []
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averages={}
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back_file = open("backup.json","w")
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back_file.write("{")
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for i in range(len(dates)):
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imgs.append(os.listdir(os.path.join('./PKLot/PKLot/PUCPR/Sunny',dates[i])))
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for i in range(len(imgs)):
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for j in range(len(imgs[i])):
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if(imgs[i][j][-4:] == ".jpg"):
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try:
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img_location = os.path.join('./PKLot/PKLot/PUCPR/Sunny',dates[i],imgs[i][j])
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locs = ET.parse(img_location[:-4] + ".xml").getroot()
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print(img_location,end=" ")
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average = calcAvg(cv2.imread(img_location),locs)
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if not(average == {}):
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averages[img_location] = average
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back_file.write("'"+img_location + "':" + str(average))
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except Exception:
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continue
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back_file.write("}")
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js = json.dumps(averages)
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print(js)
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fp = open('data.json', 'w')
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fp.write(js)
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fp.close()
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generateAvg()
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