Python cv2.FONT_HERSHEY_PLAIN Examples
The following are 30
code examples of cv2.FONT_HERSHEY_PLAIN().
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Example #1
| Source File: CThermal.py From Thermal_Image_Analysis with MIT License | 6 votes |
|
def generate_colorbar(self, min_temp=None, max_temp=None, cmap=cv.COLORMAP_JET, height=None):
if min_temp is None:
min_temp = self.global_min_temp
if max_temp is None:
max_temp = self.global_max_temp
cb_gray = np.arange(255,0,-1,dtype=np.uint8).reshape((255,1))
if cmap is not None:
cb_color = cv.applyColorMap(cb_gray, cmap)
else:
cb_color = cv.cvtColor(cb_gray, cv.COLOR_GRAY2BGR)
for i in range(1,6):
cb_color = np.concatenate( (cb_color, cb_color), axis=1 )
if height is None:
append_img = np.zeros( (self.thermal_image.shape[0], cb_color.shape[1]+30, 3), dtype=np.uint8 )
else:
append_img = np.zeros( (height, cb_color.shape[1]+30, 3), dtype=np.uint8 )
append_img[append_img.shape[0]//2-cb_color.shape[0]//2 : append_img.shape[0]//2 - (cb_color.shape[0]//2) + cb_color.shape[0] , 10 : 10 + cb_color.shape[1] ] = cb_color
cv.putText(append_img, str(min_temp), (5, append_img.shape[0]//2 - (cb_color.shape[0]//2) + cb_color.shape[0] + 30), cv.FONT_HERSHEY_PLAIN, 1, (255,0,0) , 1, 8)
cv.putText(append_img, str(max_temp), (5, append_img.shape[0]//2-cb_color.shape[0]//2-20) , cv.FONT_HERSHEY_PLAIN, 1, (0,0,255) , 1, 8 )
return append_img
Example #2
| Source File: net_utils.py From cascade-rcnn_Pytorch with MIT License | 6 votes |
|
def vis_det_and_mask(im, class_name, dets, masks, thresh=0.8):
"""Visual debugging of detections."""
num_dets = np.minimum(10, dets.shape[0])
colors_mask = random_colors(num_dets)
colors_bbox = np.round(np.random.rand(num_dets, 3) * 255)
# sort rois according to the coordinates, draw upper bbox first
draw_mask = np.zeros(im.shape[:2], dtype=np.uint8)
for i in range(1):
bbox = tuple(int(np.round(x)) for x in dets[i, :4])
mask = masks[i, :, :]
full_mask = unmold_mask(mask, bbox, im.shape)
score = dets[i, -1]
if score > thresh:
word_width = len(class_name)
cv2.rectangle(im, bbox[0:2], bbox[2:4], colors_bbox[i], 2)
cv2.rectangle(im, bbox[0:2], (bbox[0] + 18 + word_width*8, bbox[1]+15), colors_bbox[i], thickness=cv2.FILLED)
apply_mask(im, full_mask, draw_mask, colors_mask[i], 0.5)
draw_mask += full_mask
cv2.putText(im, '%s' % (class_name), (bbox[0]+5, bbox[1] + 12), cv2.FONT_HERSHEY_PLAIN,
1.0, (255,255,255), thickness=1)
return im
Example #3
| Source File: detect.py From SlowFast-Network-pytorch with MIT License | 6 votes |
|
def write(x, batches, results):
c1 = tuple(x[1:3].int())
c2 = tuple(x[3:5].int())
img = results[int(x[0])]
cls = int(x[-1])
label = "{0}".format(classes[cls])
color = random.choice(colors)
cv2.rectangle(img, c1, c2,color, 1)
t_size = cv2.getTextSize(label, cv2.FONT_HERSHEY_PLAIN, 1 , 1)[0]
c2 = c1[0] + t_size[0] + 3, c1[1] + t_size[1] + 4
cv2.rectangle(img, c1, c2,color, -1)
cv2.putText(img, label, (c1[0], c1[1] + t_size[1] + 4), cv2.FONT_HERSHEY_PLAIN, 1, [225,255,255], 1)
return img
Example #4
| Source File: video_demo_ori.py From SlowFast-Network-pytorch with MIT License | 6 votes |
|
def write(x, img):
c1 = tuple(x[1:3].int())
c2 = tuple(x[3:5].int())
cls = int(x[-1])
label = "{0}".format(classes[cls])
color = random.choice(colors)
cv2.rectangle(img, c1, c2,color, 1)
t_size = cv2.getTextSize(label, cv2.FONT_HERSHEY_PLAIN, 1 , 1)[0]
c2 = c1[0] + t_size[0] + 3, c1[1] + t_size[1] + 4
cv2.rectangle(img, c1, c2,color, -1)
cv2.putText(img, label, (c1[0], c1[1] + t_size[1] + 4), cv2.FONT_HERSHEY_PLAIN, 1, [225,255,255], 1);
return img
Example #5
| Source File: image_viewer.py From deep_sort with GNU General Public License v3.0 | 6 votes |
|
def rectangle(self, x, y, w, h, label=None):
"""Draw a rectangle.
Parameters
----------
x : float | int
Top left corner of the rectangle (x-axis).
y : float | int
Top let corner of the rectangle (y-axis).
w : float | int
Width of the rectangle.
h : float | int
Height of the rectangle.
label : Optional[str]
A text label that is placed at the top left corner of the
rectangle.
"""
pt1 = int(x), int(y)
pt2 = int(x + w), int(y + h)
cv2.rectangle(self.image, pt1, pt2, self._color, self.thickness)
if label is not None:
text_size = cv2.getTextSize(
label, cv2.FONT_HERSHEY_PLAIN, 1, self.thickness)
center = pt1[0] + 5, pt1[1] + 5 + text_size[0][1]
pt2 = pt1[0] + 10 + text_size[0][0], pt1[1] + 10 + \
text_size[0][1]
cv2.rectangle(self.image, pt1, pt2, self._color, -1)
cv2.putText(self.image, label, center, cv2.FONT_HERSHEY_PLAIN,
1, (255, 255, 255), self.thickness)
Example #6
| Source File: util.py From SlowFast-Network-pytorch with MIT License | 6 votes |
|
def draw_bboxes(img, bbox, identities=None, distance=None, speed = None, offset=(0,0)):
for i,box in enumerate(bbox):
x1,y1,x2,y2 = [int(i) for i in box]
x1 += offset[0]
x2 += offset[0]
y1 += offset[1]
y2 += offset[1]
# box text and bar
id = int(identities[i]) if identities is not None else 0
dist = distance[i]
sp = speed[i]
color = COLORS_10[id%len(COLORS_10)]
#label = '{}{}'.format("id", id)
label = '{}'.format(id)
label_dist = 'dist: {:.2f}'.format(dist)
label_sp = 'speed: {:.2f}/s'.format(sp)
t_size = cv2.getTextSize(label, cv2.FONT_HERSHEY_PLAIN, 2 , 2)[0]
dist_size = cv2.getTextSize(label_dist, cv2.FONT_HERSHEY_PLAIN, 2 , 2)[0]
sp_size = cv2.getTextSize(label_sp, cv2.FONT_HERSHEY_PLAIN, 2 , 2)[0]
cv2.rectangle(img,(x1, y1),(x2,y2),color,3)
cv2.rectangle(img,(x1, y1),(x1+t_size[0]+3,y1+t_size[1]+4), color,-1)
cv2.putText(img,label,(x1,y1+t_size[1]+4), cv2.FONT_HERSHEY_PLAIN, 2, [255,255,255], 1)
cv2.putText(img, label_dist, (x1, y1-4), cv2.FONT_HERSHEY_PLAIN, 2, [255, 255, 255], 2)
cv2.putText(img, label_sp, (x1, y1-4-dist_size[1]-4), cv2.FONT_HERSHEY_PLAIN, 2, [255, 255, 255], 2)
return img
#########################################################################################################
Example #7
| Source File: util.py From SlowFast-Network-pytorch with MIT License | 6 votes |
|
def draw_bbox(img, box, cls_name, identity=None, offset=(0,0)):
'''
draw box of an id
'''
x1,y1,x2,y2 = [int(i+offset[idx%2]) for idx,i in enumerate(box)]
# set color and label text
color = COLORS_10[identity%len(COLORS_10)] if identity is not None else COLORS_10[0]
label = '{} {}'.format(cls_name, identity)
# box text and bar
t_size = cv2.getTextSize(label, cv2.FONT_HERSHEY_PLAIN, 1 , 1)[0]
cv2.rectangle(img,(x1, y1),(x2,y2),color,2)
cv2.rectangle(img,(x1, y1),(x1+t_size[0]+3,y1+t_size[1]+4), color,-1)
cv2.putText(img,label,(x1,y1+t_size[1]+4), cv2.FONT_HERSHEY_PLAIN, 1, [255,255,255], 1)
return img
# def draw_bboxes(img, bbox, identities=None, offset=(0,0)):
# for i,box in enumerate(bbox):
# x1,y1,x2,y2 = [int(i) for i in box]
# x1 += offset[0]
# x2 += offset[0]
# y1 += offset[1]
# y2 += offset[1]
# # box text and bar
# id = int(identities[i]) if identities is not None else 0
# color = COLORS_10[id%len(COLORS_10)]
# #label = '{}{}'.format("id", id)
# label = '{}'.format(id)
# t_size = cv2.getTextSize(label, cv2.FONT_HERSHEY_PLAIN, 2 , 2)[0]
# cv2.rectangle(img,(x1, y1),(x2,y2),color,3)
# cv2.rectangle(img,(x1, y1),(x1+t_size[0]+3,y1+t_size[1]+4), color,-1)
# cv2.putText(img,label,(x1,y1+t_size[1]+4), cv2.FONT_HERSHEY_PLAIN, 2, [255,255,255], 1)
# return img
#######################################################################################################
Example #8
| Source File: bbox.py From SlowFast-Network-pytorch with MIT License | 6 votes |
|
def write(x, batches, results, colors, classes):
c1 = tuple(x[1:3].int())
c2 = tuple(x[3:5].int())
img = results[int(x[0])]
cls = int(x[-1])
label = "{0}".format(classes[cls])
color = random.choice(colors)
cv2.rectangle(img, c1, c2,color, 1)
t_size = cv2.getTextSize(label, cv2.FONT_HERSHEY_PLAIN, 1 , 1)[0]
c2 = c1[0] + t_size[0] + 3, c1[1] + t_size[1] + 4
cv2.rectangle(img, c1, c2,color, -1)
cv2.putText(img, label, (c1[0], c1[1] + t_size[1] + 4), cv2.FONT_HERSHEY_PLAIN, 1, [225,255,255], 1);
return img
Example #9
| Source File: rec-feat.py From Facial-Recognition-using-Facenet with MIT License | 6 votes |
|
def extract_face_info(img, img_rgb, database,ear):
faces = detector(img_rgb)
x, y, w, h = 0, 0, 0, 0
if len(faces) > 0:
for face in faces:
(x, y, w, h) = face_utils.rect_to_bb(face)
cv2.rectangle(img, (x, y), (x + w, y + h), (255, 255, 0), 2)
image = img[y:y + h, x:x + w]
name, min_dist = recognize_face(image, database)
if ear > thresh:
if min_dist < 0.1:
cv2.putText(img, "Face : " + name, (x, y - 50), cv2.FONT_HERSHEY_PLAIN, 1.5, (0, 255, 0), 2)
cv2.putText(img, "Dist : " + str(min_dist), (x, y - 20), cv2.FONT_HERSHEY_PLAIN, 1.5, (0, 255, 0), 2)
else:
cv2.putText(img, 'No matching faces', (x, y - 20), cv2.FONT_HERSHEY_PLAIN, 1.5, (0, 0, 255), 2)
else:
cv2.putText(img, 'Eyes Closed', (x, y - 20), cv2.FONT_HERSHEY_PLAIN, 1.5, (0, 0, 255), 2)
Example #10
| Source File: net_utils.py From cascade-rcnn_Pytorch with MIT License | 6 votes |
|
def vis_detections(im, class_name, dets, thresh=0.8):
"""Visual debugging of detections."""
for i in range(np.minimum(10, dets.shape[0])):
bbox = tuple(int(np.round(x)) for x in dets[i, :4])
score = dets[i, -1]
if score > thresh:
cv2.rectangle(im, bbox[0:2], bbox[2:4], (0, 204, 0), 2)
cv2.putText(im, '%s: %.3f' % (class_name, score), (bbox[0], bbox[1] + 15), cv2.FONT_HERSHEY_PLAIN,
1.0, (0, 0, 255), thickness=1)
return im
# Borrow from matterport mask R-CNN implementation
Example #11
| Source File: common.py From OpenCV-Python-Tutorial with MIT License | 6 votes |
|
def draw_str(dst, target, s):
x, y = target
cv2.putText(dst, s, (x+1, y+1), cv2.FONT_HERSHEY_PLAIN, 1.0, (0, 0, 0), thickness = 2, lineType=cv2.LINE_AA)
cv2.putText(dst, s, (x, y), cv2.FONT_HERSHEY_PLAIN, 1.0, (255, 255, 255), lineType=cv2.LINE_AA)
Example #12
| Source File: util.py From centerpose with MIT License | 6 votes |
|
def draw_bboxes(img, bbox, identities=None, offset=(0,0)):
for i,box in enumerate(bbox):
x1,y1,x2,y2 = [int(i) for i in box]
x1 += offset[0]
x2 += offset[0]
y1 += offset[1]
y2 += offset[1]
# box text and bar
id = int(identities[i]) if identities is not None else 0
color = COLORS_10[id%len(COLORS_10)]
label = '{} {}'.format("object", id)
t_size = cv2.getTextSize(label, cv2.FONT_HERSHEY_PLAIN, 2 , 2)[0]
cv2.rectangle(img,(x1, y1),(x2,y2),color,3)
cv2.rectangle(img,(x1, y1),(x1+t_size[0]+3,y1+t_size[1]+4), color,-1)
cv2.putText(img,label,(x1,y1+t_size[1]+4), cv2.FONT_HERSHEY_PLAIN, 2, [255,255,255], 2)
return img
Example #13
| Source File: net_utils.py From fpn.pytorch with MIT License | 6 votes |
|
def vis_det_and_mask(im, class_name, dets, masks, thresh=0.8):
"""Visual debugging of detections."""
num_dets = np.minimum(10, dets.shape[0])
colors_mask = random_colors(num_dets)
colors_bbox = np.round(np.random.rand(num_dets, 3) * 255)
# sort rois according to the coordinates, draw upper bbox first
draw_mask = np.zeros(im.shape[:2], dtype=np.uint8)
for i in range(1):
bbox = tuple(int(np.round(x)) for x in dets[i, :4])
mask = masks[i, :, :]
full_mask = unmold_mask(mask, bbox, im.shape)
score = dets[i, -1]
if score > thresh:
word_width = len(class_name)
cv2.rectangle(im, bbox[0:2], bbox[2:4], colors_bbox[i], 2)
cv2.rectangle(im, bbox[0:2], (bbox[0] + 18 + word_width*8, bbox[1]+15), colors_bbox[i], thickness=cv2.FILLED)
apply_mask(im, full_mask, draw_mask, colors_mask[i], 0.5)
draw_mask += full_mask
cv2.putText(im, '%s' % (class_name), (bbox[0]+5, bbox[1] + 12), cv2.FONT_HERSHEY_PLAIN,
1.0, (255,255,255), thickness=1)
return im
Example #14
| Source File: data.py From Sorting_Visualization with MIT License | 6 votes |
|
def Visualize(self, mark1=None, mark2=None):
img = self.figure.copy()
if mark2:
self.Mark( img, mark2, self.YELLOW)
if mark1:
self.Mark( img, mark1, self.RED)
img = cv2.resize(img, (self.im_size, self.im_size))
self.GetTime()
cv2.putText(img, self.sort_title+" Time:%02.2fs"%self.time, (20,20), cv2.FONT_HERSHEY_PLAIN, 1, self.YELLOW, 1)
if self.record:
self.vdo_wtr.write(img)
cv2.imshow(self.sort_title, img)
if self.sound and mark1:
self.PlaySound(mark1)
pass
cv2.waitKey(self.time_interval)
Example #15
| Source File: net_utils.py From FPN_Pytorch with MIT License | 6 votes |
|
def vis_det_and_mask(im, class_name, dets, masks, thresh=0.8):
"""Visual debugging of detections."""
num_dets = np.minimum(10, dets.shape[0])
colors_mask = random_colors(num_dets)
colors_bbox = np.round(np.random.rand(num_dets, 3) * 255)
# sort rois according to the coordinates, draw upper bbox first
draw_mask = np.zeros(im.shape[:2], dtype=np.uint8)
for i in range(1):
bbox = tuple(int(np.round(x)) for x in dets[i, :4])
mask = masks[i, :, :]
full_mask = unmold_mask(mask, bbox, im.shape)
score = dets[i, -1]
if score > thresh:
word_width = len(class_name)
cv2.rectangle(im, bbox[0:2], bbox[2:4], colors_bbox[i], 2)
cv2.rectangle(im, bbox[0:2], (bbox[0] + 18 + word_width*8, bbox[1]+15), colors_bbox[i], thickness=cv2.FILLED)
apply_mask(im, full_mask, draw_mask, colors_mask[i], 0.5)
draw_mask += full_mask
cv2.putText(im, '%s' % (class_name), (bbox[0]+5, bbox[1] + 12), cv2.FONT_HERSHEY_PLAIN,
1.0, (255,255,255), thickness=1)
return im
Example #16
| Source File: detect.py From pyCAIR with GNU General Public License v3.0 | 6 votes |
|
def write(x, batches, results):
c1 = tuple(x[1:3].int())
c2 = tuple(x[3:5].int())
img = results[int(x[0])]
cls = int(x[-1])
label = "{0}".format(classes[cls])
color = random.choice(colors)
cv2.rectangle(img, c1, c2,color, 1)
t_size = cv2.getTextSize(label, cv2.FONT_HERSHEY_PLAIN, 1 , 1)[0]
c2 = c1[0] + t_size[0] + 3, c1[1] + t_size[1] + 4
cv2.rectangle(img, c1, c2,color, -1)
cv2.putText(img, label, (c1[0], c1[1] + t_size[1] + 4), cv2.FONT_HERSHEY_PLAIN, 1, [225,255,255], 1)
cv2.imshow("res", img)
cv2.waitKey(0)
#cv2.imwrite("",cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
return img
Example #17
| Source File: visualization.py From MOTDT with MIT License | 6 votes |
|
def plot_detections(image, tlbrs, scores=None, color=(255, 0, 0), ids=None):
im = np.copy(image)
text_scale = max(1, image.shape[1] / 800.)
thickness = 2 if text_scale > 1.3 else 1
for i, det in enumerate(tlbrs):
x1, y1, x2, y2 = np.asarray(det[:4], dtype=np.int)
if len(det) >= 7:
label = 'det' if det[5] > 0 else 'trk'
if ids is not None:
text = '{}# {:.2f}: {:d}'.format(label, det[6], ids[i])
cv2.putText(im, text, (x1, y1 + 30), cv2.FONT_HERSHEY_PLAIN, text_scale, (0, 255, 255),
thickness=thickness)
else:
text = '{}# {:.2f}'.format(label, det[6])
if scores is not None:
text = '{:.2f}'.format(scores[i])
cv2.putText(im, text, (x1, y1 + 30), cv2.FONT_HERSHEY_PLAIN, text_scale, (0, 255, 255),
thickness=thickness)
cv2.rectangle(im, (x1, y1), (x2, y2), color, 2)
return im
Example #18
| Source File: net_utils.py From Distilling-Object-Detectors with MIT License | 6 votes |
|
def vis_detections(im, class_name, dets, thresh=0.8):
"""Visual debugging of detections."""
for i in range(np.minimum(10, dets.shape[0])):
bbox = tuple(int(np.round(x)) for x in dets[i, :4])
score = dets[i, -1]
if score > thresh:
##modify to use my draw box
#previous draw box
# cv2.rectangle(im, bbox[0:2], bbox[2:4], (0, 204, 0), 2)
# cv2.putText(im, '%s: %.3f' % (class_name, score), (bbox[0], bbox[1] + 15), cv2.FONT_HERSHEY_PLAIN,
# 3.0, (0, 0, 255), thickness=1)
draw_box(im, bbox, label=class_name, conf=score)
# im2show = cv2.resize(im, (960, 540))
# cv2.imshow('test', im2show)
# cv2.waitKey(0)
return im
Example #19
| Source File: net_utils.py From Distilling-Object-Detectors with MIT License | 6 votes |
|
def clip_gradient(model, clip_norm):
"""Computes a gradient clipping coefficient based on gradient norm."""
totalnorm = 0
clip_norm = torch.tensor([clip_norm], device='cuda')
for p in model.parameters():
if p.requires_grad:
modulenorm = p.grad.data.norm()
totalnorm += modulenorm ** 2
totalnorm = np.sqrt(totalnorm).cuda()
norm = clip_norm / max(totalnorm, clip_norm)
for p in model.parameters():
if p.requires_grad:
p.grad.mul_(norm)
#
# def vis_detections(im, class_name, dets, thresh=0.8):
# """Visual debugging of detections."""
# for i in range(np.minimum(10, dets.shape[0])):
# bbox = tuple(int(np.round(x)) for x in dets[i, :4])
# score = dets[i, -1]
# if score > thresh:
# cv2.rectangle(im, bbox[0:2], bbox[2:4], (0, 204, 0), 2)
# cv2.putText(im, '%s: %.3f' % (class_name, score), (bbox[0], bbox[1] + 15), cv2.FONT_HERSHEY_PLAIN,
# 1.0, (0, 0, 255), thickness=1)
# return im
Example #20
| Source File: rtsp_threaded_tracker.py From deep_sort_pytorch with MIT License | 6 votes |
|
def draw_boxes(img, output, offset=(0, 0)):
for i, box in enumerate(output):
x1, y1, x2, y2, identity = [int(ii) for ii in box]
x1 += offset[0]
x2 += offset[0]
y1 += offset[1]
y2 += offset[1]
# box text and bar
color = compute_color_for_labels(identity)
label = '{}{:d}'.format("", identity)
t_size = cv2.getTextSize(label, cv2.FONT_HERSHEY_PLAIN, 2, 2)[0]
cv2.rectangle(img, (x1, y1), (x2, y2), color, 3)
cv2.rectangle(img, (x1, y1), (x1 + t_size[0] + 3, y1 + t_size[1] + 4), color, -1)
cv2.putText(img, label, (x1, y1 + t_size[1] + 4), cv2.FONT_HERSHEY_PLAIN, 2, [255, 255, 255], 2)
return img
Example #21
| Source File: draw.py From deep_sort_pytorch with MIT License | 6 votes |
|
def draw_boxes(img, bbox, identities=None, offset=(0,0)):
for i,box in enumerate(bbox):
x1,y1,x2,y2 = [int(i) for i in box]
x1 += offset[0]
x2 += offset[0]
y1 += offset[1]
y2 += offset[1]
# box text and bar
id = int(identities[i]) if identities is not None else 0
color = compute_color_for_labels(id)
label = '{}{:d}'.format("", id)
t_size = cv2.getTextSize(label, cv2.FONT_HERSHEY_PLAIN, 2 , 2)[0]
cv2.rectangle(img,(x1, y1),(x2,y2),color,3)
cv2.rectangle(img,(x1, y1),(x1+t_size[0]+3,y1+t_size[1]+4), color,-1)
cv2.putText(img,label,(x1,y1+t_size[1]+4), cv2.FONT_HERSHEY_PLAIN, 2, [255,255,255], 2)
return img
Example #22
| Source File: ped_det_server.py From deep_sort_pytorch with MIT License | 6 votes |
|
def draw_boxes(self, img, frame_id, output, offset=(0, 0)):
for i, box in enumerate(output):
x1, y1, x2, y2, identity = [int(ii) for ii in box]
self.logger.add_bbox_to_frame(frame_id=frame_id,
bbox_id=identity,
top=y1,
left=x1,
width=x2 - x1,
height=y2 - y1)
x1 += offset[0]
x2 += offset[0]
y1 += offset[1]
y2 += offset[1]
# box text and bar
self.logger.add_label_to_bbox(frame_id=frame_id, bbox_id=identity, category='pedestrian', confidence=0.9)
color = compute_color_for_labels(identity)
label = '{}{:d}'.format("", identity)
t_size = cv2.getTextSize(label, cv2.FONT_HERSHEY_PLAIN, 2, 2)[0]
cv2.rectangle(img, (x1, y1), (x2, y2), color, 3)
cv2.rectangle(img, (x1, y1), (x1 + t_size[0] + 3, y1 + t_size[1] + 4), color, -1)
cv2.putText(img, label, (x1, y1 + t_size[1] + 4), cv2.FONT_HERSHEY_PLAIN, 2, [255, 255, 255], 2)
return img
Example #23
| Source File: utils.py From zmMagik with GNU General Public License v2.0 | 6 votes |
|
def write_text(frame=None, text=None, x=None,y=None, W=None, H=None, adjust=False):
(tw, th) = cv2.getTextSize(text, cv2.FONT_HERSHEY_PLAIN, fontScale=g.args['fontscale'], thickness=2)[0]
loc_x1 = x
loc_y1 = y - th - 4
loc_x2 = x + tw + 4
loc_y2 = y
if adjust:
if not W or not H:
fail_print('cannot auto adjust text as W/H not provided')
else:
if loc_x1 + tw > W:
loc_x1 = max (0, loc_x1 - (loc_x1+tw - W))
if loc_y1 + th > H:
loc_y1 = max (0, loc_y1 - (loc_y1+th - H))
cv2.rectangle(frame, (loc_x1, loc_y1), (loc_x1+tw+4,loc_y1+th+4), (0,0,0), cv2.FILLED)
cv2.putText(frame, text, (loc_x1+2, loc_y2-2), cv2.FONT_HERSHEY_PLAIN, fontScale=g.args['fontscale'], color=(255,255,255), thickness=1)
return loc_x1, loc_y1, loc_x1+tw+4,loc_y1+th+4
Example #24
| Source File: __init__.py From ImageAI with MIT License | 6 votes |
|
def draw_boxes_and_caption(self, image_frame, v_boxes, v_labels, v_scores, show_names=False, show_percentage=False):
for i in range(len(v_boxes)):
box = v_boxes[i]
y1, x1, y2, x2 = box.ymin, box.xmin, box.ymax, box.xmax
width, height = x2 - x1, y2 - y1
class_color = self.label_color(self.__labels.index(v_labels[i]))
image_frame = cv2.rectangle(image_frame, (x1, y1), (x2, y2), class_color, 2)
label = ""
if show_names and show_percentage:
label = "%s : %.3f" % (v_labels[i], v_scores[i])
elif show_names:
label = "%s" % (v_labels[i])
elif show_percentage:
label = "%.3f" % (v_scores[i])
if show_names or show_percentage:
b = np.array([x1, y1, x2, y2]).astype(int)
cv2.putText(image_frame, label, (b[0], b[1] - 10), cv2.FONT_HERSHEY_PLAIN, 1, (200, 0, 0), 3)
cv2.putText(image_frame, label, (b[0], b[1] - 10), cv2.FONT_HERSHEY_PLAIN, 1, (255, 255, 255), 2)
return image_frame
Example #25
| Source File: net_utils.py From 3d-vehicle-tracking with BSD 3-Clause "New" or "Revised" License | 6 votes |
|
def vis_detections(im, class_name, dets, gt_box, gt_center, num_box,
thresh=0.8):
"""Visual debugging of detections."""
for i in range(np.minimum(300, dets.shape[0])):
bbox = tuple(int(np.round(x)) for x in dets[i, :6])
score = dets[i, -1]
if score > thresh:
cv2.rectangle(im, bbox[0:2], bbox[2:4], (0, 204, 0), 2)
cv2.circle(im, (bbox[4], bbox[5]), 4, (0, 204, 0), -1)
cv2.putText(im, '%s: %.3f' % (class_name, score),
(bbox[0], bbox[1] + 15), cv2.FONT_HERSHEY_PLAIN,
1.0, (0, 0, 255), thickness=1)
# gt_box = gt_box[0]
# gt_center = gt_center[0]
# for i in range(num_box[0]):
# gtbox = tuple(int(np.round(x)) for x in gt_box[i, :4])
# gtcenter = tuple(x for x in gt_center[i, :2])
# cv2.rectangle(im, gtbox[0:2], gtbox[2:4], (0, 0, 204), 2)
# cv2.circle(im, (gtcenter[0], gtcenter[1]), 4, (0, 0, 204), -1)
return im
Example #26
| Source File: display.py From tensorrt_demos with MIT License | 5 votes |
|
def show_help_text(img, help_text):
"""Draw help text on image."""
cv2.putText(img, help_text, (11, 20), cv2.FONT_HERSHEY_PLAIN, 1.0,
(32, 32, 32), 4, cv2.LINE_AA)
cv2.putText(img, help_text, (10, 20), cv2.FONT_HERSHEY_PLAIN, 1.0,
(240, 240, 240), 1, cv2.LINE_AA)
return img
Example #27
| Source File: bbox_plot.py From second.pytorch with MIT License | 5 votes |
|
def cv2_draw_bbox_with_label(img,
bboxes,
colors,
labels=None,
label_colors=None,
thickness=1,
line_type=cv2.LINE_8,
font_line_type=cv2.LINE_8):
# assume bboxes has right format.
bboxes = bboxes.astype(np.int32)
if label_colors is None:
label_colors = colors
if labels is None:
labels = [None] * bboxes.shape[0]
font = cv2.FONT_ITALIC
font = cv2.FONT_HERSHEY_DUPLEX
font = cv2.FONT_HERSHEY_PLAIN
font = cv2.FONT_HERSHEY_SIMPLEX
for bbox, color, label, label_color in zip(bboxes, colors, labels,
label_colors):
color = tuple(int(c) for c in color)
label_color = tuple(int(c) for c in label_color)
cv2.rectangle(img, tuple(bbox[:2]), tuple(bbox[2:]), color, thickness,
line_type)
if label is not None:
cv2.putText(img, label, tuple(bbox[:2]), font, 1, label_color,
thickness, font_line_type, False)
return img
Example #28
| Source File: visualization.py From kaggle-rsna18 with MIT License | 5 votes |
|
def draw_caption(image, box, caption):
""" Draws a caption above the box in an image.
# Arguments
image : The image to draw on.
box : A list of 4 elements (x1, y1, x2, y2).
caption : String containing the text to draw.
"""
b = np.array(box).astype(int)
cv2.putText(image, caption, (b[0], b[1] - 10), cv2.FONT_HERSHEY_PLAIN, 1, (0, 0, 0), 2)
cv2.putText(image, caption, (b[0], b[1] - 10), cv2.FONT_HERSHEY_PLAIN, 1, (255, 255, 255), 1)
Example #29
| Source File: detector.py From VideoSearchEngine with MIT License | 5 votes |
|
def write(x, results, color):
c1 = tuple(x[1:3].int())
c2 = tuple(x[3:5].int())
img = results[int(x[0])]
cls = int(x[-1])
label = "{0}".format(classes[cls])
cv2.rectangle(img, c1, c2,color, 1)
t_size = cv2.getTextSize(label, cv2.FONT_HERSHEY_PLAIN, 1 , 1)[0]
c2 = c1[0] + t_size[0] + 3, c1[1] + t_size[1] + 4
cv2.rectangle(img, c1, c2,color, -1)
cv2.putText(img, label, (c1[0], c1[1] + t_size[1] + 4), cv2.FONT_HERSHEY_PLAIN, 1, [225,255,255], 1);
return img
Example #30
| Source File: video_demo.py From pyCAIR with GNU General Public License v3.0 | 5 votes |
|
def write(x, img):
c1 = tuple(x[1:3].int())
c2 = tuple(x[3:5].int())
cls = int(x[-1])
label = "{0}".format(classes[cls])
color = random.choice(colors)
cv2.rectangle(img, c1, c2,color, 1)
t_size = cv2.getTextSize(label, cv2.FONT_HERSHEY_PLAIN, 1 , 1)[0]
c2 = c1[0] + t_size[0] + 3, c1[1] + t_size[1] + 4
cv2.rectangle(img, c1, c2,color, -1)
cv2.putText(img, label, (c1[0], c1[1] + t_size[1] + 4), cv2.FONT_HERSHEY_PLAIN, 1, [225,255,255], 1);
return img
