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Copy pathProjectTest.py
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187 lines (171 loc) · 6.86 KB
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import os
import sys
import scipy.ndimage as nd
import matplotlib
import matplotlib.pyplot as plt
import matplotlib.patches as patches
import numpy as np
import ast
fontdict = {'fontsize':15, 'weight':'bold'}
plt.switch_backend('Qt5Agg')
class IMAGE:
def __init__(self):
self.ROIS = []
def set_image(self, im):
self.I = nd.imread(im)
self.imShape = self.I.shape
def clear_ROIS(self):
self.ROIS = []
def add_ROI(self, pos):
self.ROIS.append(pos)
def show_ROI(self, title, edgecolor, numGT, text, saveDir = None):
fig, ax = plt.subplots(1)
ax.imshow(self.I)
if(not isinstance(edgecolor,list) and len(self.ROIS) > 0):
edgecolor = [edgecolor] * len(self.ROIS)
for i in range(0,numGT):
ROI = self.ROIS[i]
rect = patches.Rectangle((ROI[0], ROI[1]), ROI[2], ROI[3], linewidth = 1, edgecolor = edgecolor[i], facecolor='none')
ax.add_patch(rect)
for i in range(numGT,len(self.ROIS)):
ROI = self.ROIS[i]
rect = patches.Rectangle((ROI[0], ROI[1]), ROI[2], ROI[3], linewidth = 1, edgecolor = edgecolor[i], facecolor='none', linestyle = '--')
ax.add_patch(rect)
if(saveDir is None):
ax.text(15,160,text, fontdict = fontdict, bbox={'facecolor':'yellow', 'edgecolor':'yellow','alpha':0.5, 'pad':2})
else:
ax.text(15, 300, text, fontdict=fontdict,bbox={'facecolor': 'yellow', 'edgecolor': 'yellow', 'alpha': 0.5, 'pad': 2})
plt.title(title)
if(not saveDir is None):
plt.savefig(os.path.join(saveDir, title), dpi = 500)
plt.close()
def close(self):
plt.close()
def IOU(boxAList, boxBList):
Th = 0.7
iou = []
matches = {}
tp = 0
fp = len(boxBList)
missed = len(boxAList)
for i in range(len(boxAList)):
boxA = boxAList[i][:4]
iou_ = []
for j in range(len(boxBList)):
boxB = boxBList[j][:4]
if(not ((boxB[0] <= boxA[0] <= boxB[0] + boxB[2]) or (boxA[0] <= boxB[0] <= boxA[0] + boxA[2]))):
iou_.append(0.0)
continue
xA = max(boxA[0], boxB[0])
yA = max(boxA[1], boxB[1])
xB = min(boxA[0] + boxA[2], boxB[0] + boxB[2])
yB = min(boxA[1] + boxA[3], boxB[1] + boxB[3])
interArea = (xB - xA + 1) * (yB - yA + 1)
boxAArea = (boxA[2] + 1)*(boxA[3] + 1)
boxBArea = (boxB[2] + 1)*(boxB[3] + 1)
iou_.append(interArea / float(boxAArea + boxBArea - interArea))
maxIou = max(iou_)
maxIouIndex = iou_.index(max(iou_))
iou.append(maxIou)
if (maxIouIndex in matches and maxIou > iou[matches[maxIouIndex]]):
if (iou[matches[maxIouIndex]] > Th and boxAList[matches[maxIouIndex]][4] == boxBList[maxIouIndex][4]):
pass
elif(maxIou > Th and boxAList[i][4] == boxBList[maxIouIndex][4]):
tp += 1
missed -= 1
fp -= 1
matches[maxIouIndex] = i
if(not maxIouIndex in matches):
matches[maxIouIndex] = i
if(maxIou > Th and boxAList[i][4] == boxBList[maxIouIndex][4]):
tp += 1
missed -= 1
fp -= 1
return tp, fp, missed, iou
def runTest(annFileNameGT, myAnnFileName, busDir , saveDir = None, elapsed = None):
image = IMAGE()
objectsColors = {'g':'1', 'y':'2', 'w':'3', 's':'4', 'b':'5', 'r':'6'}
objectsColorsInv = {v: k for k, v in objectsColors.items()}
objectsColorsForShow = {'g':'g', 'y':'y', 'w':'w', 's':'tab:gray', 'b':'b', 'r':'r'}
writtenAnnsLines = {}
annFileEstimations = open(myAnnFileName, 'r')
annFileGT = open(annFileNameGT, 'r')
writtenAnnsLines['Ground_Truth'] = (annFileGT.readlines())
writtenAnnsLines['Estimation'] = (annFileEstimations.readlines())
TP = 0
FP = 0
MISS = 0
for i in range(len(writtenAnnsLines['Ground_Truth'])):
lineGT = writtenAnnsLines['Ground_Truth'][i].replace(' ','')
colors = []
imName = lineGT.split(':')[0]
lineE = [x for x in writtenAnnsLines['Estimation'] if imName == x.split(':')[0]]
if(len(lineE) == 0):
lineE = imName + ':'
else:
lineE = lineE[0]
bus = os.path.join(busDir, imName)
image.set_image(bus)
image.clear_ROIS()
annsGT = lineGT[lineGT.index(':') + 1:].replace('\n', '')
annsE = lineE[lineE.index(':') + 1:].replace('\n', '')
annsGT = ast.literal_eval(annsGT)
if (not isinstance(annsGT, tuple)):
annsGT = [annsGT]
for ann in annsGT:
image.add_ROI(ann[:4])
colorTag = objectsColorsInv[str(ann[4])]
colors.append(objectsColorsForShow[colorTag])
numGT = len(annsGT)
if('[' in lineE):
annsE = ast.literal_eval(annsE)
if (not isinstance(annsE, tuple)):
annsE = [annsE]
for ann in annsE:
image.add_ROI(ann[:4])
colorTag = objectsColorsInv[str(ann[4])]
colors.append(objectsColorsForShow[colorTag])
tp, fp, missed, iou = IOU(annsGT, annsE)
else:
tp = 0
fp = 0
numGT = 0
missed = len(annsGT)
iou = []
TP += tp
FP += fp
MISS += missed
iouStr = ','.join(['{0:.2f}'.format(x) for x in iou])
text = 'IOU Scores : ' + iouStr + '\nTP = {}, FP = {}, Missed = {} '.format(tp, fp, missed)
image.show_ROI(edgecolor = colors, title = imName, numGT = numGT , text = text, saveDir = saveDir)
if(TP == 0):
F1Score = 0
else:
precision = TP/(TP + FP)
recall = TP/(TP + MISS)
F1Score = 2*(precision * recall)/(precision + recall)
strToWrite = 'Total detections = {}/{}\nTotal False Positives = {}\nTotal missed = {}'.format(TP, TP+MISS, FP, MISS)
strToWrite += '\nF1 SCORE : {0:.3f}'.format(F1Score)
if(not elapsed is None):
strToWrite += '\nTime elapsed : {0:.2f} seconds'.format(elapsed)
fig, ax = plt.subplots(1)
plt.title('Results', fontdict = {'fontsize':20})
im = np.zeros((10,26,3), dtype=np.uint8)
im[:,:,2] = 221
im[:,:,1] = 114
im[:,:,0] = 102
ax.imshow(im)
ax.text(4,7, strToWrite, style='italic', fontdict = {'fontsize':50, 'weight':'bold'})
mng = plt.get_current_fig_manager()
mng.window.showMaximized()
plt.show()
plt.close()
FIG, ax = plt.subplots(1)
plt.title('Results', fontdict = {'fontsize':20})
ax.imshow(im)
ax.text(2,8, strToWrite, style='italic', fontdict = {'fontsize':20, 'weight':'bold'})
if(saveDir is None):
saveDir = os.path.join(os.getcwd(), 'Output')
if(not os.path.exists(saveDir)):
os.mkdir(saveDir)
plt.savefig(os.path.join(saveDir,'Results.png'), dpi = 600)