AI Image Caption Generator

 import numpy as np

import tensorflow as tf

from tensorflow.keras.applications.inception_v3 import InceptionV3, preprocess_input

from tensorflow.keras.preprocessing import image

from tensorflow.keras.models import Model, load_model

import pickle

import cv2

import streamlit as st

from PIL import Image

# Load Pretrained InceptionV3 Model for Image Feature Extraction

base_model = InceptionV3(weights='imagenet')

model = Model(inputs=base_model.input, outputs=base_model.layers[-2].output)

# Load Pretrained Captioning Model

captioning_model = load_model("image_captioning_model.h5")

# Load Tokenizer & Word Mappings

with open("tokenizer.pickle", "rb") as handle:

    tokenizer = pickle.load(handle)

max_length = 35  # Max caption length

# Extract Features from Image

def extract_features(img_path):

    img = image.load_img(img_path, target_size=(299, 299))

    img = image.img_to_array(img)

    img = np.expand_dims(img, axis=0)

    img = preprocess_input(img)

    feature_vector = model.predict(img)

    return feature_vector

# Generate Caption

def generate_caption(img_path):

    image_features = extract_features(img_path)

    caption = "startseq"

    

    for i in range(max_length):

        sequence = [tokenizer.word_index[word] for word in caption.split() if word in tokenizer.word_index]

        sequence = tf.keras.preprocessing.sequence.pad_sequences([sequence], maxlen=max_length)

        predicted_index = np.argmax(captioning_model.predict([image_features, sequence]), axis=-1)

        word = tokenizer.index_word.get(predicted_index[0], "")

        if word == "endseq":

            break

        caption += " " + word

    

    return caption.replace("startseq", "").replace("endseq", "").strip()

# Streamlit Web Interface

st.title("🖼️ AI Image Caption Generator")

uploaded_file = st.file_uploader("Upload an image...", type=["jpg", "png", "jpeg"])

if uploaded_file is not None:

    img = Image.open(uploaded_file)

    st.image(img, caption="Uploaded Image", use_column_width=True)

    

    # Save the uploaded image temporarily

    img_path = "temp.jpg"

    img.save(img_path)

    

    # Generate Caption

    with st.spinner("Generating Caption..."):

        caption_text = generate_caption(img_path)

    

    st.subheader("📝 Generated Caption:")

    st.write(caption_text)