def visualization(val_data, idx, grasps_pre, grasps_true):
#最开始的几个迭代过程中不会有q_img值足够大的预测出现，所以，此时提出不出有效的抓取，进而是不会有visuaization出现的
img = Image.from_file(val_data.dataset.rgbf[idx])
left = val_data.dataset._get_crop_attrs(idx)[1]
top = val_data.dataset._get_crop_attrs(idx)[2]
img.crop((left, top), (left + 300, top + 300))
a = img.img
a_points = grasps_pre[0].as_gr.points.astype(np.uint8) #预测出的抓取
b_points = grasps_true.points
color1 = (255, 255, 0)
color2 = (255, 0, 0)
for i in range(3):
img = cv2.line(a, tuple(a_points[i]), tuple(a_points[i + 1]),
color1 if i % 2 == 0 else color2, 1)
img = cv2.line(a, tuple(a_points[3]), tuple(a_points[0]), color2, 1)
color1 = (0, 0, 0)
color2 = (0, 255, 0)
for b_point in b_points:
for i in range(3):
img = cv2.line(a, tuple(b_point[i]), tuple(b_point[i + 1]),
color1 if i % 2 == 0 else color2, 1)
img = cv2.line(a, tuple(b_point[3]), tuple(b_point[0]), color2, 1)
#cv2.imshow('img',a)
cv2.imwrite('img.png', a)
def get_rgb(self, idx):
'''
:功能 :读取返回指定id的rgb图像
:参数 idx :int,要读取的数据id
:返回 :ndarray,处理好后的rgb图像
'''
rgb_img = Image.from_file(self.rgbf[idx])
rgb_img.normalize()
center, left, top = self._get_crop_attrs(idx)
rgb_img.crop((left, top),
(left + self.output_size, top + self.output_size))
return rgb_img.img
def get_rgb(self, idx, rot=0, zoom=1.0, normalize=True):
rgb_img = Image.from_file(self.rgbf[idx])
center, left, top = self._get_crop_attrs(idx)
#先旋转后裁剪再缩放最后resize
rgb_img.rotate(rot, center)
rgb_img.crop((top, left), (min(
480, top + self.output_size), min(640, left + self.output_size)))
rgb_img.zoom(zoom)
rgb_img.resize((self.output_size, self.output_size))
if normalize:
rgb_img.normalize()
rgb_img.img = rgb_img.img.transpose((2, 0, 1))
return rgb_img.img
def get_rgb(self,idx,rot = 0,zoom = 1.0,normalize = True):
'''
:功能 :读取返回指定id的rgb图像
:参数 idx :int,要读取的数据id
:返回 :ndarray,处理好后的rgb图像
'''
rgb_img = Image.from_file(self.rgbf[idx])
rgb_img.rotate(rot)
rgb_img.zoom(zoom)
#注意，这里暂且不论是否zoom，图像是直接由（1024X1024）resize成为了(300X300)的，相应的抓取框标注也必须进行同样程度的“resize”或者说缩放（scale）才行
rgb_img.resize((self.output_size, self.output_size))
if normalize:
rgb_img.normalize()
rgb_img.img = rgb_img.img.transpose((2, 0, 1))
#这里还有一句transpose没写，先不管
return rgb_img.img
def get_rgb(self,idx,rot=0, zoom=1.0):
'''
:功能 :读取返回指定id的rgb图像
:参数 idx :int,要读取的数据id
:返回 :ndarray,处理好后的rgb图像
'''
rgb_img = Image.from_file(self.rgbf[idx])
rgb_img.normalize()
center,left,top = self._get_crop_attrs(idx)
#先旋转后裁剪再缩放最后resize
rgb_img.rotate(rot,center)
rgb_img.crop((left,top),(left+self.output_size,top+self.output_size))
rgb_img.zoom(zoom)
rgb_img.resize((self.output_size, self.output_size))
return rgb_img.img
