def run():
fileList = os.listdir(cfg.resultsFolder)
resultsFileList = filter(lambda element: '.result' in element, fileList)
for resultsFile in resultsFileList:
resultsFilePath = cfg.resultsFolder + '/' +resultsFile
file = open(resultsFilePath, 'r')
imageResults = pickle.load(file)
boxes = imageResults['bboxes']
scores = imageResults['scores']
imagepath = imageResults['imagepath']
filename = os.path.basename(imagepath)
if boxes is None:
print 'No pedestrians found for image '+imagepath
continue
print 'Saving results for image '+filename
idx = np.where(scores > cfg.decision_threshold)
boxes = boxes[idx]
scores = scores[idx]
boxes, scores = nms.non_max_suppression_fast(boxes, scores, overlapthresh= cfg.nmsOverlapThresh)
img = Image.open(imagepath)
#Show the results on a colored image
img = drawing.drawResultsOnImage(img, boxes, scores)
io.imsave('Results/'+filename, img)
file.close()
print 'Finished!'
def run():
fileList = os.listdir(cfg.resultsFolder)
resultsFileList = filter(lambda element: '.result' in element, fileList)
for resultsFile in resultsFileList:
resultsFilePath = cfg.resultsFolder + '/' +resultsFile
file = open(resultsFilePath, 'rb')
imageResults = pickle.load(file)
boxes = imageResults['bboxes']
scores = imageResults['scores']
imagepath = imageResults['imagepath']
filename = os.path.basename(imagepath)
if boxes is None:
print ('No pedestrians found for image '+imagepath)
continue
print ('Saving results for image '+filename)
idx = np.where(scores > cfg.decision_threshold)
boxes = boxes[idx]
scores = scores[idx]
boxes, scores = nms.non_max_suppression_fast(boxes, scores, overlapthresh= cfg.nmsOverlapThresh)
img = Image.open(imagepath)
#Show the results on a colored image
img = drawing.drawResultsOnImage(img, boxes, scores)
img.save('Results/'+filename,"PNG")
file.close()
print ('Finished!')
def run():
imagePath = 'Images/Image001.png'
bboxes, scores = detector.testImage(imagePath, applyNMS=True)
img = Image.open(imagePath)
img = drawing.drawResultsOnImage(img, bboxes, scores)
if platform.system() is 'Windows':
plt.imshow(img) #img.show() does not work properly on windows. We upse matplotlib.imshow instead
plt.show()
else:
img.show()
def run():
imagePath = 'Images/Image001.png'
bboxes, scores = detector.testImage(imagePath, applyNMS=True)
img = Image.open(imagePath)
img = drawing.drawResultsOnImage(img, bboxes, scores)
if platform.system() is 'Windows':
plt.imshow(
img
) #img.show() does not work properly on windows. We upse matplotlib.imshow instead
plt.show()
else:
img.show()
def run():
if cfg.exp_methodology == 2:
#Check which one is the negative class (background)
negclass = cfg.data.index(cfg.negative_Class)
#Open results file, it contains the 'candidates' structure.
file = open(cfg.resultsFolder + '/Ce_ccl.results', 'r')
candidates = pickle.load(file)
if candidates['bboxes'] is None:
print 'No signals found'
else:
#for each image in cfg.testFolderPath
extension = '.jpg'
#For each stored bounding box
imagepath = ''
img = None
for index in range(0, len(candidates['bboxes'])):
i_image = candidates['bboxes'][index][0]
i_box = candidates['bboxes'][index][-4:]
i_prediction = candidates['prediction'][index]
if int(i_prediction) != int(
negclass
): # Do not print boxes predicted as background
predicted_sign = cfg.data[int(i_prediction)]
real_sign = cfg.data[int(candidates['bboxes'][index][1])]
results_curr_img_path = 'Results/' + i_image + extension
if os.path.isfile(results_curr_img_path): # If exists
#print 'exist!'
imagepath = results_curr_img_path
else:
#print 'NOT exist!'
imagepath = cfg.testFolderPath + '/' + i_image + extension
img = Image.open(imagepath)
if img is not None:
print 'Drawing results on ' + i_image + extension
img = drawing.drawResultsOnImage(
img, i_box, predicted_sign, real_sign)
io.imsave(results_curr_img_path, img)
file.close()
def run():
start_time = time.time()
imagePath = 'Images/im.jpg'
bboxes, scores = detector.testImage(imagePath, applyNMS=True)
img = Image.open(imagePath)
img = drawing.drawResultsOnImage(img, bboxes, scores)
print 'Finish process. Ready to plot'
print("Finish Process --- %s seconds ---" % (time.time() - start_time))
if platform.system() is 'Windows':
plt.imshow(
img
) #img.show() does not work properly on windows. We upse matplotlib.imshow instead
plt.show()
else:
img.show()
def run(): if cfg.exp_methodology == 2: #Check which one is the negative class (background) negclass = cfg.data.index(cfg.negative_Class) #Open results file, it contains the 'candidates' structure. file = open(cfg.resultsFolder+'/Ce_ccl.results', 'r') candidates = pickle.load(file) if candidates['bboxes'] is None: print 'No signals found' else: #for each image in cfg.testFolderPath extension = '.jpg' #For each stored bounding box imagepath = ''; img = None; for index in range(0, len(candidates['bboxes'])): i_image = candidates['bboxes'][index][0] i_box = candidates['bboxes'][index][-4:] i_prediction = candidates['prediction'][index] if int(i_prediction) != int(negclass): # Do not print boxes predicted as background predicted_sign = cfg.data[int(i_prediction)] real_sign = cfg.data[int(candidates['bboxes'][index][1])] results_curr_img_path = 'Results/' + i_image + extension if os.path.isfile(results_curr_img_path): # If exists #print 'exist!' imagepath = results_curr_img_path; else: #print 'NOT exist!' imagepath = cfg.testFolderPath + '/' + i_image + extension; img = Image.open(imagepath) if img is not None: print 'Drawing results on ' + i_image + extension img = drawing.drawResultsOnImage(img, i_box, predicted_sign, real_sign) io.imsave(results_curr_img_path, img) file.close()
