feat: Updated src/api.py

src/api.py

@@ -1,15 +1,19 @@
+"""
+This module is used to serve a FastAPI application that predicts the digit in an uploaded image using a trained PyTorch model.
+"""
+
 from fastapi import FastAPI, UploadFile, File
 from PIL import Image
 import torch
 from torchvision import transforms
 from main import Net # Importing Net class from main.py
 
-# Load the model
+# Load the trained PyTorch model
 model = Net()
 model.load_state_dict(torch.load("mnist_model.pth"))
-model.eval()
+model.eval() # Set the model to evaluation mode
 
-# Transform used for preprocessing the image
+# Define the transform used for preprocessing the image
 transform = transforms.Compose([
  transforms.ToTensor(),
  transforms.Normalize((0.5,), (0.5,))
@@ -19,10 +23,28 @@
 
 @app.post("/predict/")
 async def predict(file: UploadFile = File(...)):
+ """
+ Predicts the digit in the uploaded image using the trained PyTorch model.
+ 
+ Parameters:
+ file: The uploaded image file.
+ 
+ Returns:
+ A dictionary with the predicted digit.
+ """
+ # Open the image file and convert it to grayscale
  image = Image.open(file.file).convert("L")
+
+ # Preprocess the image using the defined transform
  image = transform(image)
+
+ # Add a batch dimension to the image
  image = image.unsqueeze(0) # Add batch dimension
+
+ # Predict the digit in the image without computing gradients
  with torch.no_grad():
  output = model(image)
  _, predicted = torch.max(output.data, 1)
+
+ # Return the prediction as a dictionary
  return {"prediction": int(predicted[0])}