i use custom HaarCasscade to train my model at this address "https://www.cs.auckland.ac.nz/~m.rezaei/Tutorials/Creating_a_Cascade_of_Haar-Like_Classifiers_Step_by_Step.pdf"

1.Faces detect

- my model with 35 images positive, 400 images negative (i dont have data and my computer not strong to train)
- Evaluation model (work on data set :(( )

- With IOU = 0.5, set model scaleFactors(multiScale) = 1.01 (1%)
ReCall: 65.7% , TP = 23, sum = 35
Predection: 95.83%, TP = 23 and FP = 1

- With IOU = 0.5, set mode; scaleFactors(multiScale) = 1.05 (5%)
ReCall: 40% , TP = 14, sum = 35
Predection: 100%, TP = 14 and FP = 0

2. Number-Plate-motobike detect (private)

- my model with 200 positive, 400 images negative (special condition)
- Evaluation model (work on data set :(( )

- With IOU = 0.5, set model scaleFactors(multiScale) = 1.01 (1%)
ReCall: 73.68% , TP = 154 and sum = 209
Predection: 96.85% , TP = 154 and FPS = 5

- With IOU = 0.5, set model scaleFactors(multiScale) = 1.05 (5%)
ReCall: 29.19% , TP = 61 and sum = 209
Predection: 95.31% , TP = 61 and FP = 3

3. Number-Plate-cars detect

- my model with 100 positive, 200 images negative (special condition)
- Evaluation model (work on data set :(( )

- With IOU = 0.5, set model scaleFactors(multiScale) = 1.01 (1%)
Recall: 50% , TP = 50 and sum = 100
Predection: 13.97% , TP = 50 and FP = 308

- With IOU = 0.5, set model scaleFactors(multiScale) = 1.05 (5%)
Recall: 51% , TP = 51 and sum = 100
Predection: 20.9% , TP = 51 and FP = 163

Note: Result so bad cause by the conditions of images
compare to result of haarcascade_russian_plate_number (on my data)

• With IOU = 0.5, set model scaleFactors(multiScale) = 1.01 (1%)
  Recall: 43% , TP = 44 and sum = 108
  Predection: 12.29% , TP = 44 and FP = 314
  
  
• With IOU = 0.5, set model scaleFactors(multiScale) = 1.05 (5%)
  Recall: 35% , TP = 38 and sum = 108
  Predection: 17.35% , TP = 38 and FP = 181
  

4. Number-Plate-cars detect combine detect text by OCR

OCR-75% or 75% that mean OCR read correct 75% OCR or 100% that mean OCR read correct 100%

This show data Recall

This show data Recall of OCR via tesseract

This show data Recall of special conditions and add more funtions in code