From e65c915e5bdbcca56b37aa13bcff4911beffbe37 Mon Sep 17 00:00:00 2001
From: hyhmrright <hyhmrright@163.com>
Date: 星期五, 31 五月 2019 13:13:35 +0800
Subject: [PATCH] change py2 to py3
---
code/test_on_video_dlib.py | 35 +++++++++++++++++++----------------
1 files changed, 19 insertions(+), 16 deletions(-)
diff --git a/code/test_on_video_dlib.py b/code/test_on_video_dlib.py
index d03415f..eefced7 100644
--- a/code/test_on_video_dlib.py
+++ b/code/test_on_video_dlib.py
@@ -58,12 +58,12 @@
# Dlib face detection model
cnn_face_detector = dlib.cnn_face_detection_model_v1(args.face_model)
- print 'Loading snapshot.'
+ print('Loading snapshot.')
# Load snapshot
saved_state_dict = torch.load(snapshot_path)
model.load_state_dict(saved_state_dict)
- print 'Loading data.'
+ print ('Loading data.')
transformations = transforms.Compose([transforms.Scale(224),
transforms.CenterCrop(224), transforms.ToTensor(),
@@ -71,13 +71,13 @@
model.cuda(gpu)
- print 'Ready to test network.'
+ print('Ready to test network.')
# Test the Model
model.eval() # Change model to 'eval' mode (BN uses moving mean/var).
total = 0
- idx_tensor = [idx for idx in xrange(66)]
+ idx_tensor = [idx for idx in range(66)]
idx_tensor = torch.FloatTensor(idx_tensor).cuda(gpu)
video = cv2.VideoCapture(video_path)
@@ -98,9 +98,13 @@
# fourcc = cv2.cv.CV_FOURCC(*'MJPG')
# out = cv2.VideoWriter('output/video/output-%s.avi' % args.output_string, fourcc, 30.0, (width, height))
+ txt_out = open('output/video/output-%s.txt' % args.output_string, 'w')
+
frame_num = 1
while frame_num <= args.n_frames:
+ print(frame_num)
+
ret,frame = video.read()
if ret == False:
break
@@ -112,24 +116,23 @@
for idx, det in enumerate(dets):
# Get x_min, y_min, x_max, y_max, conf
- x_min = d.rect.left()
- y_min = d.rect.top()
- x_max = d.rect.right()
- y_max = d.rect.bottom()
- conf = d.confidence
- print x_min, y_min, x_max, y_max, conf
+ x_min = det.rect.left()
+ y_min = det.rect.top()
+ x_max = det.rect.right()
+ y_max = det.rect.bottom()
+ conf = det.confidence
- if conf > 0.95:
+ if conf > 1.0:
bbox_width = abs(x_max - x_min)
bbox_height = abs(y_max - y_min)
- x_min -= 3 * bbox_width / 4
- x_max += 3 * bbox_width / 4
+ x_min -= 2 * bbox_width / 4
+ x_max += 2 * bbox_width / 4
y_min -= 3 * bbox_height / 4
y_max += bbox_height / 4
x_min = max(x_min, 0); y_min = max(y_min, 0)
x_max = min(frame.shape[1], x_max); y_max = min(frame.shape[0], y_max)
# Crop image
- img = cv2_frame[y_min:y_max,x_min:x_max]
+ img = cv2_frame[int(y_min):int(y_max),int(x_min):int(x_max)]
img = Image.fromarray(img)
# Transform
@@ -155,8 +158,8 @@
# Plot expanded bounding box
# cv2.rectangle(frame, (x_min, y_min), (x_max, y_max), (0,255,0), 1)
- out.write(frame)
- frame_num += 1
+ out.write(frame)
+ frame_num += 1
out.release()
video.release()
--
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