compute the iou, slice picture etc.
Project description
ai_tool
ai tool
slice picture
from ai_tool.img_slide import yield_sub_img # yield the sub image from the jpg for bbox, sub_img in yield_sub_img("test.jpg", 0, 0, 180, 60): clip = "-".join([str(x) for x in bbox]) print("sub img:{}".format(clip)) cv2.imshow(clip, sub_img) cv2.waitKey(0)
IoU
compute the iou for tow boxes,
example box1 1, 2, 101, 102. location(1,2) is left-up, location(101,102) is right-down.
from ai_tool.bbox import BBox bbox1 = BBox([1, 2, 101, 102]) bbox2 = BBox([11, 12, 121, 122]) iou = bbox1 / bbox2 print("iou", iou) assert iou > 0.5 print('box1 S is', bbox1.S) print('box1 & box2', bbox1 & bbox2) print('box1 == box2', bbox1 == bbox2) print('merge box1 + box2', bbox1 + bbox2) print('merge box1 | box2', bbox1 | bbox2)
result is :
iou 0.5785714285714286 box1 S is 10000 box1 & box2 [11, 12, 101, 102] box1 == box2 True merge box1 + box2 [1, 2, 121, 122] merge box1 | box2 [1, 2, 121, 122]
multi bbox operation
from ai_tool.bbox import BBoxes, BBox bb1 = BBoxes(iou_thresh=0.6) bb2 = BBoxes() bb1.append([1,2, 101, 102]) bb1.append([1000, 2, 1101, 102]) bb2.append([11, 12, 111, 112]) bb2.append([1, 1002, 101, 1102]) # judge the bbox in bb1 print("[5, 5, 100, 100] in bb1", BBox([5, 5, 100, 100]) in bb1) print("[100, 5, 200, 100] in bb1", BBox([100, 5, 200, 100]) in bb1) # bb1 & bb2 print("bb1 & bb2", bb1 & bb2) print("bb1 - bb2", bb1 - bb2) print("bb2 - bb1", bb2 - bb1)
result is
[5, 5, 100, 100] in bb1 True [100, 5, 200, 100] in bb1 False bb1 & bb2 [[1, 2, 101, 102]] bb1 - bb2 [[1000, 2, 1101, 102]] bb2 - bb1 [[1, 1002, 101, 1102]]
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