Model Pipeline - Pre-trained detection models
This pipeline uses a pre-trained detection model to find objects in images. It takes an image, processes it, and outputs boxes around detected objects with labels and confidence scores.
0
0
Pre-trained detection models in Computer Vision - Model Pipeline Trace
Data Flow - 6 Stages
1Input Image
1 image x 640 x 480 x 3 channels→Load and resize image to fixed size→1 image x 640 x 480 x 3 channels
A photo of a street with cars and people
↓
2Preprocessing
1 image x 640 x 480 x 3 channels→Normalize pixel values to 0-1 range→1 image x 640 x 480 x 3 channels
Pixel values changed from 0-255 to 0.0-1.0
↓
3Feature Extraction
1 image x 640 x 480 x 3 channels→Pass image through convolutional layers of pre-trained backbone→1 feature map x 40 x 30 x 512 channels
Extracted edges and shapes like wheels and faces
↓
4Region Proposal
1 feature map x 40 x 30 x 512 channels→Generate candidate boxes where objects might be→1000 candidate boxes x 4 coordinates
Boxes around possible cars, people, signs
↓
5Classification and Refinement
1000 candidate boxes x 4 coordinates→Classify each box and adjust box size→Top 100 boxes with class labels and confidence scores
Box #23 labeled 'car' with 0.92 confidence
↓
6Non-Maximum Suppression
Top 100 boxes with labels and scores→Remove overlapping boxes to keep best ones→Final 10 boxes with labels and confidence
One box per detected car or person
Training Trace - Epoch by Epoch
Loss
2.5 |*
2.0 | *
1.5 | *
1.0 | *
0.5 | **
0.0 +---------
1 5 10 15 20 Epochs
| Epoch | Loss ↓ | Accuracy ↑ | Observation |
|---|---|---|---|
| 1 | 2.5 | 0.30 | Model starts learning basic object features |
| 5 | 1.2 | 0.55 | Model improves detecting common objects |
| 10 | 0.8 | 0.70 | Model refines box predictions and labels |
| 15 | 0.5 | 0.82 | Model converges with good detection accuracy |
| 20 | 0.45 | 0.85 | Minor improvements, stable performance |
Prediction Trace - 6 Layers
Layer 1: Input Image
Layer 2: Preprocessing
Layer 3: Feature Extraction
Layer 4: Region Proposal
Layer 5: Classification and Refinement
Layer 6: Non-Maximum Suppression
Model Quiz - 3 Questions
Test your understanding
What is the main purpose of the region proposal stage?
Key Insight
Pre-trained detection models speed up object detection by using learned features from large datasets. They propose many possible object locations, classify them, and then keep only the best boxes to accurately detect objects in new images.