Image Recognition with Deep Learning Frameworks
Image Recognition with Deep Learning Frameworks Image recognition is at the heart of many real-world AI applications—from facial recognition to autonomous vehicles. In this post, we'll walk through building an image recognition system using Python-based deep learning frameworks like TensorFlow and PyTorch. We'll also touch on integrating it with a Java backend using REST APIs. 🚀 Tools & Frameworks TensorFlow / PyTorch – for deep learning model development Flask – for serving the model as an API Java (Spring Boot) – to consume the image recognition service 🧰 Step 1: Training or Using a Pretrained Model We'll use a pretrained model like ResNet50 from TensorFlow or PyTorch's torchvision. 🧠Using ResNet50 with TensorFlow import tensorflow as tf from tensorflow.keras.applications import resnet50 from tensorflow.keras.preprocessing import image import numpy as np model = resnet50.ResNet50(weights='im...