def main():
folder = "../../../dataset/images"
value_file = folder + "/bases.txt"
imgs, files = sc.read_imgs(folder)
values = sc.read_values(value_file)
threshes = sc.saturation_process(imgs)
finals = []
totals = []
scores = []
for (img, thresh, file, value) in zip(imgs, threshes, files, values):
total, final = sc.find_contour(img, thresh)
score = sc.f1_measure(value, total)
finals.append(final)
totals.append(total)
scores.append(score)
save = zip(files, imgs, threshes, finals, values, totals, scores)
rate = np.sum(scores) / len(scores)
for (file, img, thresh, final, value, total, score) in save:
print(
"Filename: %s, Detected objects: %d, Actual value: %d, Score: %5.3f"
% (file, total, value, score))
print(
"\n ######## \n ######## \n Average success in this batch: %5.3f \n" %
(rate))
def main():
folder = "../../../Opencv_Test/DataSet1" #"../../../dataset/images"
value_file = folder + "/bases.txt"
imgs, files = sc.read_imgs(folder)
values = sc.read_values(value_file)
threshes = sc.saturation_process(imgs)
finals = []
totals = []
scores = []
recalls = []
precisions = []
for (img, thresh, file, value) in zip(imgs, threshes, files, values):
total, final = sc.blob_detection(img, thresh)
score, recall, precision = sc.f1_measure(value, total)
finals.append(final)
totals.append(total)
scores.append(score)
recalls.append(recall)
precisions.append(precision)
save = zip(files, imgs, threshes, finals, values, totals, scores, recalls, precisions)
rate = np.sum(scores) / len (scores)
rate_r = np.sum(recalls) / len (recalls)
rate_p = np.sum(precisions) / len (precisions)
for (file, img, thresh, final, value, total, score, recall, precision) in save:
print("Filename: %s, Detected objects: %d, Actual value: %d, Score: %5.3f" % (file, total, value, score))
print("\n ######## \n ######## \n Average success in this batch: %5.3f \n Average recall: %5.3f \n Average precision: %5.3f" % (rate, rate_r, rate_p))
