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14 changes: 8 additions & 6 deletions HumanDetector/body_detector/detector.py
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Original file line number Diff line number Diff line change
@@ -1,3 +1,5 @@
# veena

import numpy as np
from skimage.feature import corner_harris, corner_peaks
from skimage.transform import pyramid_gaussian
Expand Down Expand Up @@ -34,7 +36,7 @@ def sliding_window(image, window_size, step_size):
def detector(filename):
im = cv2.imread(filename)
im = imutils.resize(im, width = min(400, im.shape[1]))
min_wdw_sz = (64, 128)
minimum_window_size = (64, 128)
step_size = (10, 10)
downscale = 1.25

Expand All @@ -47,10 +49,10 @@ def detector(filename):

for im_scaled in pyramid_gaussian(im, downscale = downscale):
#The list contains detections at the current scale
if im_scaled.shape[0] < min_wdw_sz[1] or im_scaled.shape[1] < min_wdw_sz[0]:
if im_scaled.shape[0] < minimum_window_size[1] or im_scaled.shape[1] < minimum_window_size[0]:
break
for (x, y, im_window) in sliding_window(im_scaled, min_wdw_sz, step_size):
if im_window.shape[0] != min_wdw_sz[1] or im_window.shape[1] != min_wdw_sz[0]:
for (x, y, im_window) in sliding_window(im_scaled, minimum_window_size, step_size):
if im_window.shape[0] != minimum_window_size[1] or im_window.shape[1] != minimum_window_size[0]:
continue
im_window = color.rgb2gray(im_window)
fd = hog(im_window, orientations, pixels_per_cell, cells_per_block, visualize, normalize)
Expand All @@ -62,8 +64,8 @@ def detector(filename):

if clf.decision_function(fd) > 0.5:
detections.append((int(x * (downscale**scale)), int(y * (downscale**scale)), clf.decision_function(fd),
int(min_wdw_sz[0] * (downscale**scale)),
int(min_wdw_sz[1] * (downscale**scale))))
int(minimum_window_size[0] * (downscale**scale)),
int(minimum_window_size[1] * (downscale**scale))))



Expand Down