Bounding box representation in Computer Vision - Model Pipeline Trace

Model Pipeline - Bounding box representation

This pipeline shows how images with objects are processed to detect and represent objects using bounding boxes. Bounding boxes are rectangles that mark where objects are in the image.

Data Flow - 5 Stages

1Input Image

1 image of 640 x 480 pixels x 3 color channels→Raw image loaded for object detection→1 image of 640 x 480 pixels x 3 color channels

A photo showing a dog and a cat

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2Preprocessing

1 image of 640 x 480 x 3→Resize image to 320 x 320 and normalize pixel values to 0-1→1 image of 320 x 320 x 3

Resized and normalized image ready for model input

↓

3Feature Extraction

1 image of 320 x 320 x 3→Extract features using convolutional layers→1 tensor of 20 x 20 x 256 features

Feature map highlighting edges and shapes

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4Bounding Box Prediction

1 tensor of 20 x 20 x 256→Predict bounding box coordinates and class scores→1 tensor of 20 x 20 x 6 (4 box coords + 2 class scores)

Predicted boxes like [x_center, y_center, width, height] and scores for dog/cat

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5Postprocessing

1 tensor of 20 x 20 x 6→Apply threshold and non-maximum suppression to filter boxes→List of 3 bounding boxes with coordinates and class labels

Boxes: Dog at (150, 200, 100, 80), Cat at (300, 220, 90, 70)

Training Trace - Epoch by Epoch

Loss
2.5 |*****
2.0 |**** 
1.5 |***  
1.0 |**   
0.5 |*    
0.0 +-----
      1 2 3 4 5 Epochs

Epoch	Loss ↓	Accuracy ↑	Observation
1	2.5	0.30	High loss and low accuracy as model starts learning
2	1.8	0.45	Loss decreases, accuracy improves with initial learning
3	1.2	0.60	Model learns bounding box locations better
4	0.8	0.75	Good improvement in detecting objects
5	0.5	0.85	Model converges with low loss and high accuracy

Prediction Trace - 4 Layers

Layer 1: Input Image

Layer 2: Feature Extraction

Layer 3: Bounding Box Prediction

Layer 4: Postprocessing

Model Quiz - 3 Questions

What does a bounding box represent in object detection?

A A color filter applied to the image

B A rectangle marking where an object is in the image

C A label describing the whole image

D A pixel brightness adjustment

Key Insight

Bounding box representation helps the model locate objects by predicting rectangles around them. Training improves the model's ability to predict accurate boxes, shown by decreasing loss and increasing accuracy.