def check_typical(self, idx, rot, zoom):
grs = Grasps.load_from_jacquard_files(
self.graspf[idx],
scale=self.output_size / 1024.0) #因为图像每个都resize了，所以这里每个抓取框都要缩放
c = self.output_size // 2
grs.rotate(rot, (c, c))
grs.zoom(zoom, (c, c))
# 下面是新加的代码,用于测试典型学习的内容
angles = [round(gr.angle, 1) for gr in grs.grs]
angle_dict = dict(Counter(angles))
list1, list2 = (list(t) for t in zip(
*sorted(zip(angle_dict.values(), angle_dict.keys()))))
first = list1[-1]
if len(list1) > 1:
second = list1[-2]
total = first + second
else:
total = first
percent = (total) / len(grs.grs)
if percent > 0.70:
# 生成样例学习
angle_shift = 0.2
typical1_min = list2[-1] - angle_shift
typical1_max = list2[-1] + angle_shift
if len(list1) > 1:
typical2_min = list2[-2] - angle_shift
typical2_max = list2[-2] + angle_shift
else:
typical2_min = 0
typical2_max = 0
grs1 = []
grs2 = []
grs3 = []
for gr in grs.grs[::]:
if gr.angle < typical1_max and gr.angle > typical1_min:
grs1.append(gr)
elif gr.angle < typical2_max and gr.angle > typical2_min:
grs2.append(gr)
else:
grs3.append(gr)
grasp_true1 = Grasps(grs1)
# grasp_true2 = Grasps(grs2)
# grasp_true3 = Grasps(grs3)
return percent, grasp_true1
return percent, Grasps(grs)
def get_grasp(self,idx,rot = 0,zoom=1.0):
grs = Grasps.load_from_jacquard_files(self.graspf[idx],scale = self.output_size/1024.0)#因为图像每个都resize了，所以这里每个抓取框都要缩放
c = self.output_size//2
grs.rotate(rot,(c,c))
grs.zoom(zoom,(c,c))
pos_img,angle_img,width_img = grs.generate_img(self.output_size,self.output_size)
return pos_img,angle_img,width_img
def get_raw_grasps(self, idx, rot=0, zoom=1.0):
raw_grasps = Grasps.load_from_cornell_files(self.graspf[idx])
center, left, top = self._get_crop_attrs(idx)
# 这是paddlepaddel这里报错而专门加的一句，rot.sequeeze()
raw_grasps.rotate(rot.squeeze(), center)
raw_grasps.offset((-top, -left))
raw_grasps.zoom(zoom, (self.output_size // 2, self.output_size // 2))
return raw_grasps
def get_grasp(self,idx,rot = 0,zoom=1.0):
grs = Grasps.load_from_jacquard_files(self.graspf[idx],scale = self.output_size/1024.0)#因为图像每个都resize了，所以这里每个抓取框都要缩放
c = self.output_size//2
grs.rotate(rot,(c,c))
grs.zoom(zoom,(c,c))
pos_img,angle_img,width_img = grs.generate_img(self.output_size,self.output_size)
# poto_data = (pos_grid_img,gt_points, gt_angles, gt_widths,gt_lengths)
poto_data = grs.generate_grid_mask(shape = (self.output_size,self.output_size))
return pos_img,angle_img,width_img,poto_data
def _get_crop_attrs(self, idx):
grasp_rectangles = Grasps.load_from_cornell_files(self.graspf[idx])
center = grasp_rectangles.center
left = max(
0, min(center[1] - self.output_size // 2, 640 - self.output_size))
top = max(
0, min(center[0] - self.output_size // 2, 480 - self.output_size))
return center, left, top
def get_raw_grasps(self,idx,rot = 0,zoom = 1.0):
'''
:功能 :读取返回指定id的抓取框信息斌进行一系列预处理(裁剪，缩放等)后以Grasps对象的形式返回
:参数 idx :int,要读取的数据id
:返回 :Grasps，此id中包含的抓取
'''
raw_grasps = Grasps.load_from_jacquard_files(self.graspf[idx],scale = self.output_size/1024.0)
c = self.output_size//2
raw_grasps.rotate(rot,(c,c))
raw_grasps.zoom(zoom,(c,c))
return raw_grasps
def get_raw_grasps(self, idx):
'''
:功能 :读取返回指定id的抓取框信息斌进行一系列预处理(裁剪，缩放等)后以Grasps对象的形式返回
:参数 idx :int,要读取的数据id
:返回 :Grasps，此id中包含的抓取
'''
raw_grasps = Grasps.load_from_cornell_files(self.graspf[idx])
center, left, top = self._get_crop_attrs(idx)
raw_grasps.offset((-left, -top))
return raw_grasps
def get_grasp(self, idx, rot=0, zoom=1.0):
grs = Grasps.load_from_cornell_files(self.graspf[idx])
center, left, top = self._get_crop_attrs(idx)
#先旋转再偏移再缩放
grs.rotate(rot, center)
grs.offset((-top, -left))
grs.zoom(zoom, (self.output_size // 2, self.output_size // 2))
pos_img, angle_img, width_img = grs.generate_img(
shape=(self.output_size, self.output_size))
return pos_img, angle_img, width_img
def get_raw_grasps(self,idx,rot = 0.0,zoom = 1.0):
'''
:功能 :读取返回指定id的抓取框信息斌进行一系列预处理(裁剪，缩放等)后以Grasps对象的形式返回
:参数 idx :int,要读取的数据id
:返回 :Grasps，此id中包含的抓取
'''
raw_grasps = Grasps.load_from_cornell_files(self.graspf[idx])
center, left, top = self._get_crop_attrs(idx)
raw_grasps.rotate(rot,center)
raw_grasps.offset((-top,-left))
raw_grasps.zoom(zoom,(self.output_size//2,self.output_size//2))
return raw_grasps
def _get_crop_attrs(self, idx):
'''
:功能 :读取多抓取框中心点的坐标，并结合output_size计算要裁剪的左上角点坐标
:参数 idx :int,
:返回 :计算出来的多抓取框中心点坐标和裁剪区域左上角点坐标
'''
grasp_rectangles = Grasps.load_from_cornell_files(self.graspf[idx])
center = grasp_rectangles.center
#按照ggcnn里面的话，这里本该加个限制条件，防止角点坐标溢出边界，但前面分析过，加不加区别不大，就不加了
left = center[0] - self.output_size // 2
top = center[1] - self.output_size // 2
return center, left, top
def _get_crop_attrs(self,idx):
'''
:功能 :读取多抓取框中心点的坐标，并结合output_size计算要裁剪的左上角点坐标
:参数 idx :int,
:返回 :计算出来的多抓取框中心点坐标和裁剪区域左上角点坐标
'''
grasp_rectangles = Grasps.load_from_cornell_files(self.graspf[idx])
center = grasp_rectangles.center
#按照ggcnn里面的话，这里本该加个限制条件，防止角点坐标溢出边界，但前面分析过，加不加区别不大，就不加了
#分析错误，后面出现bug了，所以还是加上吧
left = max(0, min(center[1] - self.output_size // 2, 640 - self.output_size))
top = max(0, min(center[0] - self.output_size // 2, 480 - self.output_size))
return center,left,top#the center (column,row) must be changed to for later rotate considerations
def get_grasp(self, idx):
'''
:功能 :读取返回指定id的抓取标注参数并将多个抓取框的参数返回融合
:参数 idx :int,要读取的数据id
:返回 :以图片的方式返回定义一个抓取的多个参数，包括中心点，角度，宽度和长度，同时返回idx，方便后面validate的时候查找真实的抓取框用
'''
grs = Grasps.load_from_cornell_files(self.graspf[idx])
grs.offset((-(grs.center[0] - self.output_size // 2),
-(grs.center[1] - self.output_size // 2)))
pos_img, angle_img, width_img = grs.generate_img(
shape=(self.output_size, self.output_size))
return pos_img, angle_img, width_img
def get_grasp(self,idx,rot=0, zoom=1.0):
'''
:功能 :读取返回指定id的抓取标注参数并将多个抓取框的参数返回融合
:参数 idx :int,要读取的数据id
:返回 :以图片的方式返回定义一个抓取的多个参数，包括中心点，角度，宽度和长度，同时返回idx，方便后面validate的时候查找真实的抓取框用
'''
grs = Grasps.load_from_cornell_files(self.graspf[idx])
center, left, top = self._get_crop_attrs(idx)
#先旋转再偏移再缩放
grs.rotate(rot,center)
grs.offset((-top,-left))
grs.zoom(zoom,(self.output_size//2,self.output_size//2))
pos_img,angle_img,width_img = grs.generate_img(shape = (self.output_size,self.output_size))
return pos_img,angle_img,width_img
def show_grasp(img, grasp, color=(0, 255, 0)):
# 给定一张图及一个抓取(Grasps和Grasp类型均可),在图上绘制出抓取框
if not isinstance(grasp, Grasps):
grasp = Grasps([grasp])
for gr in grasp.grs:
# 有时候预测出负值会报错
try:
for i in range(3):
cv2.line(img, tuple(gr.points.astype(np.uint32)[i][::-1]),
tuple(gr.points.astype(np.uint32)[i + 1][::-1]),
color, 1)
cv2.line(img, tuple(gr.points.astype(np.uint32)[3][::-1]),
tuple(gr.points.astype(np.uint32)[0][::-1]), color, 1)
except:
pass
return img
def get_grasp(self, idx):
'''
:功能 :读取返回指定id的抓取标注参数并将多个抓取框的参数返回融合
:参数 idx :int,要读取的数据id
:参数 pos :bool,是否生成返回位置映射图
:参数 angle :bool,是否生成返回角度映射图
:参数 width :bool,是否生成返回夹爪宽度映射图
:返回 :以图片的方式返回定义一个抓取的多个参数，包括中心点，角度，宽度和长度
'''
grs = Grasps.load_from_cornell_files(self.graspf[idx])
grs.offset((-(grs.center[0] - self.output_size // 2),
-(grs.center[1] - self.output_size // 2)))
pos_img, angle_img, width_img = grs.generate_img(
shape=(self.output_size, self.output_size))
return pos_img, angle_img, width_img
def get_grasp(self, idx, rot=0, zoom=1.0):
grs = Grasps.load_from_jacquard_files(
self.graspf[idx],
scale=self.output_size / 1024.0) #因为图像每个都resize了，所以这里每个抓取框都要缩放
c = self.output_size // 2
grs.rotate(rot, (c, c))
grs.zoom(zoom, (c, c))
# 下面是新加的代码,用于测试典型学习的内容
percent, grasp_true1 = self.check_typical(idx, rot, zoom)
if percent > 0.70:
pos_img, angle_img, width_img = grasp_true1.generate_img_n(
self.output_size, self.output_size)
else:
# 不是的话啥都不用做
pos_img, angle_img, width_img = grs.generate_img(
self.output_size, self.output_size)
return pos_img, angle_img, width_img
