pamudu123 / Fashion_Trend_Analyzer

The Fashion Trend Analyzer is designed to identify and record seasonal costume patterns among different age groups and genders.

Fashion Trend Analyzer

The Fashion Trend Analyzer is designed to identify and record seasonal costume patterns among different age groups and genders.

1. People Detection and Tracking

• Detection Model: YOLOv8 segmentation model.
• Tracking Algorithm: ByteTrack Algorithm.
• Count: Records the number of people entering (IN) and leaving (OUT).

When a person is entering:

• Segmentation Mask Retrieval: The system fetches the segmentation mask.
• Body Division:
  • The detected person image is divided into three sections based on predefined ratios:
    1. Head Part
    2. Upper Costume Part
    3. Lower Costume Part

2. Age and Gender Prediction (Head Region)

• Models:
  • Uses two separate models for age and gender prediction.
  • Due to real-time application needs, a lightweight model ("coffee model") is employed.
  • For enhanced speed, the model is quantized to INT8.
• Age Categories:
  • The age model can predict the following age categories: '(0-2)', '(4-6)', '(8-12)', '(15-20)', '(25-32)', '(38-43)', '(48-53)', '(60-100)'.
• Gender Prediction:
  • The gender model can predict whether the detected person is Male or Female.

3. Costume Color Detection (Upper and Lower Costume Regions)

• Algorithm: Uses KMeans algorithm-based method for identify colours.
• Steps:
  1. Image Conversion: Converts from BGR to RGB using OpenCV.
  2. Preprocessing:The black background pixels in the pixel mask are removed.
  3. K-Means Clustering: Groups similar pixels (colors) into clusters.
  4. Cluster Analysis: Retrieves the cluster centers representing the most common colors.
  5. Pixel Count: Calculates the number of pixels in each cluster.
  6. Percentage Calculation: Determines the percentage of each color cluster in the image.
  7. Most Common Color Values: Generates a list of common RGB color values along with their respective percentages.
  8. RGB2HSV: Converts the RGB color values to the HSV color format.
  9. Determine Respective Color: Based on the HSV values, the respective color is determined.

4. Data Storage

• Excel: All the records are saved in an Excel file.
• Database: Records are also stored in a MySQL database for reference.

5. Display

• The details, including segmentation masks, are displayed in an OpenCV window.

Demonstration

Video 1

Video 2