app.py

from fastapi import FastAPI, UploadFile, File
import uvicorn
import tensorflow as tf
from tensorflow import keras
from keras import models
from PIL import Image
from io import BytesIO
import numpy as np
import cv2

# Some constants to be used in the program
IMG_SIZE = (32,32)
APP_HOST = '127.0.1.1'
APP_PORT = '5000'

# Character mapping for the character prediction
char_map = {
    0:'𑑐(0)',   1:'𑑑(1)',    2:'𑑒(2)',   3:'𑑓(3)',      4: '𑑔(4)',     5: '𑑕(5)',    6: '𑑖(6)',    7: '𑑗(7)',
    8:'𑑘(8)',   9:'𑑙(9)',    10:'𑑉(OM)', 11:'𑐀(A)',    12: '𑐁(AA)',   13: '𑐀𑑅(AH)',  14: '𑐂(I)',    
    15:'𑐃(II)',16:'𑐄(U)',   17:'𑐅(UU)',  18:'𑐆(R)',    19: '𑐆𑐺(RR)',  20: '𑐊(E)',   21: '𑐋(AI)',    22: '𑐌(O)',    
    23:'𑐍(AU)', 24:'𑐈(L)',  25:'𑐉(LL)',   26:'𑐎(KA)',   27: '𑐎𑑂𑐳(KSA)', 28: '𑐏(KHA)',29: '𑐐(GA)',    30: '𑐑(GHA)',    
    31:'𑐒(NGA)',32:'𑐔(CA)',  33:'𑐕(CHA)', 34:'𑐖(JA)',   35: '𑐖𑑂𑐘(JñA)',  36: '𑐗(JHA)',37: '𑐗(JHA-alt)',38: '𑐘(NYA)',    
    39:'𑐚(TA)', 40:'𑐛(TTHA)', 41:'𑐜(DDA)', 42:'𑐝(DHA)',  43: '𑐞(NNA)', 44: '𑐟(TA)',  45: '𑐟𑑂𑐬(TRA)',    46: '𑐠(THA)',
    47:'𑐡(DA)', 49:'𑐣(NA)',   50:'𑐥(PA)',  51:'𑐦(PHA)',  52: '𑐧(BA)',  53: '𑐨(BHA)',  54: '𑐩(MA)',    55: '𑐫(YA)', 
    56:'𑐬(RA)', 57: '𑐮(LA)', 58:'𑐰(WA)', 59:'𑐱(SHA)',    60: '𑐱(SHA-alt)', 61: '𑐲(SSA)',    62: '𑐳(SA)', 63: '𑐴(HA)'
}



# Importing the model
model = models.load_model('vgg.h5')


# Defining the FastAPI instance here
app = FastAPI()

# Function for reading image
def file_to_array(data) -> np.ndarray:
    image = np.array(Image.open(BytesIO(data)))

    return image 


@app.get('/')
async def root_func():
    return {'message': 'this is the root function'}


@app.post('/predict_image')
async def upload_image(file: UploadFile = File(...)):
    image  = Image.open(BytesIO(await file.read()))

    image  = cv2.resize(np.array(image), IMG_SIZE)
    image  = image.astype('float32')
    image  = np.expand_dims(image, axis=0)

    output = model.predict(image)
    result = char_map[np.argmax(output)]
    
    return {'prediction': result}


    
if __name__ == "__main__":
    uvicorn.run(app, host=APP_HOST, port=APP_PORT)