from pybx import anchor, ops
+
+image_sz = (256, 256)
+feature_sz = (10, 10)
+asp_ratio = 1/2.
+
+coords, labels = anchor.bx(image_sz, feature_sz, asp_ratio)
+
+
+
+
+
+
+
+PyBx
+Installation
+pip install pybxUsage
+To calculate the anchor boxes for a single feature size and aspect ratio, given the image size:
+
+
+
+100 anchor boxes of asp_ratio 0.5 is generated along with unique labels:
+
+
+len(coords), len(labels)
+
+(100, 100)The anchor box labels are especially useful, since they are pretty descriptive:
+
+
+
+coords[-1], labels[-1]
+
+([234, 225, 252, 256], 'a_10x10_0.5_99')To calculate anchor boxes for multiple feature sizes and aspect ratios, we use anchor.bxs instead:
+
+
+feature_szs = [(10, 10), (8, 8)]
+asp_ratios = [1., 1/2., 2.]
+
+coords, labels = anchor.bxs(image_sz, feature_szs, asp_ratios)All anchor boxes are returned as ndarrays of shape (N,4) where N is the number of boxes.
The box labels are even more important now, since they help you uniquely identify to which feature map size or aspect ratios they belong to.
+
+
+
+coords[101], labels[101]
+
+(array([29, 0, 47, 30]), 'a_10x10_0.5_1')
+
+
+coords[-1], labels[-1]
+
+(array([217, 228, 256, 251]), 'a_8x8_2.0_63')MultiBx methods
+Box coordinates (with/without labels) in any format (usually ndarray, list, json, dict) can be instantialized as a MultiBx, exposing many useful methods and attributes of MultiBx. For example to calculate the area of each box iteratively:
+
+
+from pybx.basics import *
+# passing anchor boxes and labels from anchor.bxs()
+print(coords.shape)
+
+boxes = mbx(coords, labels)
+type(boxes)
+
+(492, 4)
+
+pybx.basics.MultiBx
+
+
+len(boxes)
+
+492
+
+
+areas = [b.area for b in boxes]Each annotation in the MultiBx object boxes is also a BaseBx with its own set of methods and properties.
+
+
+boxes[-1]
+
+BaseBx(coords=[[217, 228, 256, 251]], label=['a_8x8_2.0_63'])
+
+
+boxes[-1].coords, boxes[-1].label
+
+([[217, 228, 256, 251]], (#1) ['a_8x8_2.0_63'])MultiBx objects can also be “added” which stacks them vertically to create a new MultiBx object:
+
+
+boxes_true = mbx(coords_json) # annotation as json records
+len(boxes_true)
+
+2
+
+
+boxes_anchor = mbx(coords_numpy) # annotation as ndarray
+len(boxes_anchor)
+
+492
+
+
+boxes_true
+
+MultiBx(coords=[[130, 63, 225, 180], [13, 158, 90, 213]], label=['clock', 'frame'])
+
+
+boxes = boxes_true + boxes_anchor + boxes_true
+
+
+len(boxes)
+
+496Use ground truth boxes for model training
+
+
+
+from pybx.anchor import get_gt_thresh_iou, get_gt_max_iou
+from pybx.vis import VisBx
+
+
+image_sz
+
+(256, 256)
+
+
+boxes_true
+
+MultiBx(coords=[[130, 63, 225, 180], [13, 158, 90, 213]], label=['clock', 'frame'])Calculate candidate anchor boxes for many aspect ratios and scales.
+
+
+
+feature_szs = [(10, 10), (3, 3), (2, 2)]
+asp_ratios = [0.3, 1/2., 2.]
+
+anchors, labels = anchor.bxs(image_sz, feature_szs, asp_ratios)Wrap using pybx methods. This step is not necessary but convenient.
+
+
+
+boxes_anchor = get_bx(anchors, labels)
+len(boxes_anchor)
+
+341The following function returns two positive ground truth anchors with largest IOU for each class in the label bounding boxes passed.
+
+
+
+gt_anchors, gt_ious, gt_masks = get_gt_max_iou(
+ true_annots=boxes_true,
+ anchor_boxes=boxes_anchor, # if plain numpy, pass anchor_boxes and anchor_labels
+ update_labels=False, # whether to replace ground truth labels with true labels
+ positive_boxes=1, # can request extra boxes
+)
+
+
+gt_anchors
+
+{'clock': BaseBx(coords=[[156, 0, 227, 180]], label=['a_2x2_0.3_1']),
+ 'frame': BaseBx(coords=[[12, 152, 72, 256]], label=['a_3x3_0.5_6'])}
+
+
+all_gt_anchors = gt_anchors['clock'] + gt_anchors['frame']
+all_gt_anchors
+
+/mnt/data/projects/pybx/pybx/basics.py:464: BxViolation: Change of object type imminent if trying to add <class 'pybx.basics.BaseBx'>+<class 'pybx.basics.BaseBx'>. Use <class 'pybx.basics.BaseBx'>+<class 'pybx.basics.BaseBx'> instead or basics.stack_bxs().
+ f"Change of object type imminent if trying to add "
+
+MultiBx(coords=[[156, 0, 227, 180], [12, 152, 72, 256]], label=['a_2x2_0.3_1', 'a_3x3_0.5_6'])
+
+
+v = VisBx(pth='../data/', img_fn='image.jpg', image_sz=image_sz)
+v.show(all_gt_anchors, color={'a_2x2_0.3_1':'red', 'a_3x3_0.5_6': 'red'})
+
+<AxesSubplot:>
+
+
More exploratory stuff in the walkthrough notebook!
+ + +