Computer Vision with OpenCV: AI Image Recognition Basics

Computer Vision with OpenCV: AI Image Recognition Basics

💡 What You Will Learn

Computer Vision with OpenCV: AI Image Recognition Basics

|:----|:----|:--------|:----| | OpenCV | 4.10+ | pip install opencv-python | ~30MB | | HuggingFace Transformers | 4.48+ | pip install transformers | ~15MB | | PyTorch | 2.5+ | pip install torch ||

import cv2
import numpy as np

# 
img = cv2.imread('photo.jpg')
print(f": {img.shape}")  # (, , )

# 
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# Canny
edges = cv2.Canny(gray, 50, 150)

# 
cv2.imshow('Original', img)
cv2.imshow('Edges', edges)
cv2.waitKey(0)
cv2.destroyAllWindows()
cv2.imwrite('edges_output.jpg', edges)

from transformers import pipeline

# 500MB
classifier = pipeline("image-classification", model="google/vit-base-patch16-224")

result = classifier("photo.jpg")
print(result)
# [{'label': 'golden retriever', 'score': 0.95}, ...]

|:----|:-------------|:----------|:---------| ||| ResNet50/ViT>90% | +30% | || Haar Cascade~80% | MTCNN/RetinaFace>99% | +19% |

import cv2
from facenet_pytorch import MTCNN
import torch

device = 'cuda' if torch.cuda.is_available() else 'cpu'
detector = MTCNN(keep_all=True, device=device)

cap = cv2.VideoCapture(0)
while True:
    ret, frame = cap.read()
    if not ret:
        break
    boxes, probs = detector.detect(frame)
    if boxes is not None:
        for box, prob in zip(boxes, probs):
            if prob > 0.9:
                x1, y1, x2, y2 = [int(v) for v in box]
                cv2.rectangle(frame, (x1,y1), (x2,y2), (0,255,0), 2)
                cv2.putText(frame, f'{prob:.2f}', (x1,y1-10),
                            cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0,255,0), 2)
    cv2.imshow('Face Detection', frame)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break
cap.release()
cv2.destroyAllWindows()

from paddleocr import PaddleOCR
ocr = PaddleOCR(use_angle_cls=True, lang='ch')
result = ocr.ocr('receipt.jpg')
for line in result[0]:
    print(f": {line[1][0]}, : {line[1][1]:.2f}")
# 
# : , : 0.98
# : : ¥1,280.00, : 0.96