I have an image where I am creating rectangle over a specified area. The image is :
I am reading this image passing it through yolo algorithm gives me co-ordinates for rectangle around this gesture the x1 , y1 , x2 , y2 values are
print(x1 , y1 , x2 , y2)
tensor(52.6865) tensor(38.8428) tensor(143.1934) tensor(162.9857)
Using these to add a rectangle over the image
box_w = x2 - x1
box_h = y2 - y1
color = bbox_colors[int(np.where(unique_labels == int(cls_pred))[0])]
# Create a Rectangle patch
bbox = patches.Rectangle((x1, y1), box_w, box_h, linewidth=2, edgecolor=color, facecolor="none")
# Add the bbox to the plot
ax.add_patch(bbox)
It results in the follwing image :
Now, I want to blacken everything around this square. For this purpose i am saving the above image and reading it back then using opencv to blacken the rest using following code.
x1 = int(x1)
y1 = int(y1)
x2 = int(x2)
y2 = int(y2)
# read image
img = cv2.imread(output_path)
#creating black mask
mask = np.zeros_like(img)
mask = cv2.rectangle(mask, (x1, y1), (x2,y2), (255,255,255), -1)
# apply mask to image
result = cv2.bitwise_and(img, mask)
# save results
cv2.imwrite(output_path, result)
I am getting the following image as result :
There are 2 issues :
- cv2.rectangle only takes integer values as co-ordinates
- May be x, y axis has different direction in yolo and open cv. Just guessing cause integers co-ordinate values should not be giving such vast difference from the rectangle.
This is being done in Jupyter notebook on Win 10.
