In Faster R-CNN, the bounding box predictions are generated by the Region Proposal Network (RPN) based on the anchors. The RPN predicts adjustments to the anchor boxes to obtain more accurate bounding box coordinates. The formulas for calculating the bounding box coordinates using anchors are as follows:
In simple way
def calculate_final_bbox(anchor, rpn_predictions):
x_anchor, y_anchor, w_anchor, h_anchor = anchor
delta_x, delta_y, delta_w, delta_h = rpn_predictions
x_adjusted = x_anchor + delta_x * w_anchor
y_adjusted = y_anchor + delta_y * h_anchor
w_adjusted = w_anchor * np.exp(delta_w)
h_adjusted = h_anchor * np.exp(delta_h)
x_final = x_adjusted - w_adjusted / 2
y_final = y_adjusted - h_adjusted / 2
return x_final, y_final, w_adjusted, h_adjusted
# Example usage:
anchor_box = (10, 20, 30, 40)
rpn_predictions = (0.1, -0.2, 0.3, -0.1)
final_bbox = calculate_final_bbox(anchor_box, rpn_predictions)
print("Final Bounding Box:", final_bbox)
Make sure to replace the anchor_box and rpn_predictions variables with the actual values from your model's output. The final_bbox variable will contain the calculated bounding box coordinates.
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