Lullooo/SiameseCNN-ImgMatching

🔢 Siamese CNN: Number Recognition & Similarities

Note: See model performances and examples here 📈 <br/><br/>

🎯 PURPOSES

This project aims to develop a Siamese Neural Network 🧠 able to match and identify different kinds of numerical digits 🔢. The model learns to measure how similar two images are rather than directly classifying them. This makes it suitable for tasks like:

• —🤝 Digits matching and recognition: Compare the uploaded digits with those in the test set. Once a match is found, label the uploaded digit with the same label as the matched one.
• —🔓 Security unlocking mechanisms: The camera captures an istant image of a face or an object. If the similarity with those in the training pool is high, it unlocks the device/program.
• —🔎 Duplicate detection: Define a similarity score between the external image and those in the reference set. If similarity with one of these is high, it is likely is a duplicate. <br/><br/>

🛠️ WORKFLOW

The workflow is quite straightforward: the user is prompted to upload a picture of a number or to draw it in a canvas, and the Siamese Network returns:

• —1️⃣ Which digit is the uploaded/drawn picture (The uploaded img is a ...) along with its similarity score.
• —2️⃣ 3 matching pics coming from the testing dataset. <br/><br/>

⚠️ WARNINGS

Be fully aware of the model's limitations by reading the model limitations doc ✋ <br/><br/>

🧠 MODEL OVERVIEW

The Siamese architecture leverages shared convolutional layers to extract features from two images, then computes their Euclidean distance in embedding space. A contrastive loss function is employed:

&nbsp;&nbsp;*L = (1 - Y) (1/2) D^2 + Y (1/2) (max(0, m - D))^2*

with:

• —D: distance between embeddings
• —Y = 0 for similar and Y = 1 for dissimilar
• —m: margin parameters (can be changed) <br/><br/>

Note: I got the idea to implement this kind of network for this kind of task + some code chunks from the Daily Dose of Data Science newsletter 📨. They are really awesome, and everyone interested in data science should check them too 😉.

Note2: As this was a work-related project, it has been approved for posting, and all sensitive information and data are omitted to protect privacy. Code snippet containing sensitive data has not been posted. __________________________________________________________________________________________________________