diff --git a/.gitattributes b/.gitattributes
index a6344aac8c09253b3b630fb776ae94478aa0275b..10a913c7dbf63705a486cd7710f4cf72b294e063 100644
--- a/.gitattributes
+++ b/.gitattributes
@@ -33,3 +33,77 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+Flowers/Amaryllis.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Anemone.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Aster.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Azalea[[:space:]](Rhododendron).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Bachelor_s[[:space:]]Button[[:space:]](Centaurea[[:space:]]cyanus).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Balloon[[:space:]]Flower[[:space:]](Platycodon[[:space:]]grandiflorus).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Begonia.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Bird[[:space:]]of[[:space:]]Paradise[[:space:]](Strelitzia).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Black-Eyed[[:space:]]Susan[[:space:]](Rudbeckia[[:space:]]hirta).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Bleeding[[:space:]]Heart.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Bluebell.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Buttercup.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Butterfly[[:space:]]Bush[[:space:]](Buddleja).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Butterfly[[:space:]]Weed[[:space:]](Asclepias[[:space:]]tuberosa).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Calla[[:space:]]Lily.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Camellia.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Canterbury[[:space:]]Bells[[:space:]](Campanula[[:space:]]medium).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Carnation.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Chrysanthemum.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Columbine[[:space:]](Aquilegia).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Coneflower[[:space:]](Echinacea).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Cosmos.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Crocus[[:space:]](Crocus).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Cyclamen[[:space:]](Cyclamen).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Daffodil.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Dahlia.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Daisy.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Daylily[[:space:]](Hemerocallis).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Delphinium[[:space:]](Delphinium).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Forget-Me-Not.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Foxglove.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Freesia.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Fuchsia.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Gaillardia[[:space:]](Gaillardia).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Gentian[[:space:]](Gentiana).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Geranium.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Gerbera[[:space:]]Daisy[[:space:]](Gerbera).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Gladiolus.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Gloriosa[[:space:]]Lily[[:space:]](Gloriosa).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Hellebore.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Hibiscus.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Hollyhock[[:space:]](Alcea).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Hoya[[:space:]](Hoya).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Hyacinth.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Hydrangea[[:space:]](Hydrangea).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Iceland[[:space:]]Poppy[[:space:]](Papaver[[:space:]]nudicaule).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Iris.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Jasmine.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Lavender.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Lily.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Marigold.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Monkshood[[:space:]](Aconitum).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Morning[[:space:]]Glory[[:space:]](Ipomoea).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Nasturtium[[:space:]](Tropaeolum).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Orchid[[:space:]]Cactus[[:space:]](Epiphyllum).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Orchid.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Oxalis[[:space:]](Oxalis).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Pansy.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Peony.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Periwinkle[[:space:]](Vinca).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Poppy.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Primrose[[:space:]](Primula).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Queen[[:space:]]Anne_s[[:space:]]Lace[[:space:]](Daucus[[:space:]]carota).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Ranunculus.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Rhododendron[[:space:]](Rhododendron).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Rose.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Rudbeckia[[:space:]](Rudbeckia).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Scabiosa[[:space:]](Scabiosa).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Shasta[[:space:]]Daisy[[:space:]](Leucanthemum).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Snapdragon.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Snowdrop[[:space:]](Galanthus).png filter=lfs diff=lfs merge=lfs -text
+Flowers/Sunflower.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Tulip.png filter=lfs diff=lfs merge=lfs -text
+Flowers/Zinnia.png filter=lfs diff=lfs merge=lfs -text
diff --git a/100flowers.txt b/100flowers.txt
new file mode 100644
index 0000000000000000000000000000000000000000..4f06e71bbc036b260c5c131890a242019bde289e
--- /dev/null
+++ b/100flowers.txt
@@ -0,0 +1,100 @@
+Rose (Rosa)
+Tulip (Tulipa)
+Lily (Lilium)
+Sunflower (Helianthus)
+Daisy (Bellis perennis)
+Orchid (Orchidaceae)
+Daffodil (Narcissus)
+Peony (Paeonia)
+Marigold (Tagetes)
+Hydrangea (Hydrangea)
+Pansy (Viola tricolor)
+Poppy (Papaver)
+Carnation (Dianthus)
+Gerbera Daisy (Gerbera)
+Iris (Iridaceae)
+Lavender (Lavandula)
+Chrysanthemum (Chrysanthemum)
+Amaryllis (Hippeastrum)
+Zinnia (Zinnia)
+Forget-Me-Not (Myosotis)
+Cosmos (Cosmos)
+Ranunculus (Ranunculus)
+Bleeding Heart (Dicentra)
+Camellia (Camellia)
+Foxglove (Digitalis)
+Freesia (Freesia)
+Anemone (Anemone)
+Snapdragon (Antirrhinum)
+Calla Lily (Zantedeschia)
+Hollyhock (Alcea)
+Gladiolus (Gladiolus)
+Sweet Pea (Lathyrus odoratus)
+Delphinium (Delphinium)
+Bird of Paradise (Strelitzia)
+Columbine (Aquilegia)
+Bleeding Heart (Dicentra)
+Nasturtium (Tropaeolum)
+Azalea (Rhododendron)
+Columbine (Aquilegia)
+Sweet William (Dianthus barbatus)
+Bachelor's Button (Centaurea cyanus)
+Canterbury Bells (Campanula medium)
+Balloon Flower (Platycodon grandiflorus)
+Gaillardia (Gaillardia pulchella)
+Hellebore (Helleborus)
+Delphinium (Delphinium)
+Hibiscus (Hibiscus)
+Rudbeckia (Rudbeckia)
+Monkshood (Aconitum)
+Butterfly Weed (Asclepias tuberosa)
+Black-Eyed Susan (Rudbeckia hirta)
+Dahlia (Dahlia)
+Bleeding Heart (Dicentra)
+Snowdrop (Galanthus)
+Hoya (Hoya)
+Cyclamen (Cyclamen)
+Gloriosa Lily (Gloriosa)
+Hellebore (Helleborus)
+Daylily (Hemerocallis)
+Butterfly Bush (Buddleja)
+Chrysanthemum (Chrysanthemum)
+Coneflower (Echinacea)
+Crocus (Crocus)
+Fuchsia (Fuchsia)
+Gaillardia (Gaillardia)
+Gentian (Gentiana)
+Iceland Poppy (Papaver nudicaule)
+Queen Anne's Lace (Daucus carota)
+Monkshood (Aconitum)
+Morning Glory (Ipomoea)
+Orchid Cactus (Epiphyllum)
+Oxalis (Oxalis)
+Peony (Paeonia)
+Periwinkle (Vinca)
+Primrose (Primula)
+Rhododendron (Rhododendron)
+Scabiosa (Scabiosa)
+Shasta Daisy (Leucanthemum)
+Statice (Limonium)
+Stock (Matthiola)
+Strawflower (Xerochrysum)
+Sweet Alyssum (Lobularia)
+Toad Lily (Tricyrtis)
+Torch Lily (Kniphofia)
+Trillium (Trillium)
+Veronica (Veronica)
+Viola (Viola)
+Wallflower (Erysimum)
+Water Lily (Nymphaea)
+Yarrow (Achillea)
+Ylang Ylang (Cananga odorata)
+Geranium (Pelargonium)
+Gloriosa Daisy (Rudbeckia hirta)
+Jacob's Ladder (Polemonium)
+Japanese Anemone (Anemone hupehensis)
+Johnny Jump Up (Viola tricolor)
+Lantana (Lantana)
+Love-in-a-Mist (Nigella damascena)
+Maranta (Maranta)
+Money Plant (Lunaria annua)
\ No newline at end of file
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diff --git a/Flowers/Aster.png b/Flowers/Aster.png
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diff --git a/Flowers/Bachelor_s Button (Centaurea cyanus).png b/Flowers/Bachelor_s Button (Centaurea cyanus).png
new file mode 100644
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diff --git a/Flowers/Balloon Flower (Platycodon grandiflorus).png b/Flowers/Balloon Flower (Platycodon grandiflorus).png
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diff --git a/Flowers/Begonia.png b/Flowers/Begonia.png
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diff --git a/Flowers/Calla Lily.png b/Flowers/Calla Lily.png
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diff --git a/Flowers/Camellia.png b/Flowers/Camellia.png
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diff --git a/Flowers/Carnation.png b/Flowers/Carnation.png
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diff --git a/Flowers/Chrysanthemum.png b/Flowers/Chrysanthemum.png
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diff --git a/Flowers/Columbine (Aquilegia).png b/Flowers/Columbine (Aquilegia).png
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diff --git a/Flowers/Coneflower (Echinacea).png b/Flowers/Coneflower (Echinacea).png
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diff --git a/Flowers/Cosmos.png b/Flowers/Cosmos.png
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diff --git a/Flowers/Cyclamen (Cyclamen).png b/Flowers/Cyclamen (Cyclamen).png
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diff --git a/Flowers/Daffodil.png b/Flowers/Daffodil.png
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diff --git a/Flowers/Zinnia.png b/Flowers/Zinnia.png
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diff --git a/openai_api_key_llm_2023.txt b/openai_api_key_llm_2023.txt
new file mode 100644
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+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
\ No newline at end of file
diff --git a/text_to_image_demo.py b/text_to_image_demo.py
new file mode 100644
index 0000000000000000000000000000000000000000..3e690eaec9ff81f9db2d89694997ac27d0316262
--- /dev/null
+++ b/text_to_image_demo.py
@@ -0,0 +1,218 @@
+# -*- coding: utf-8 -*-
+"""Text_to_Image_Demo.ipynb
+
+Automatically generated by Colaboratory.
+
+Original file is located at
+    https://colab.research.google.com/drive/1mkGloXbrNHKFh99ryB6PQDyCJ3u4RqD5
+
+## Generate Images from Text
+"""
+# Important installations
+# pip install openai
+# pip install python-dotenv
+# pip install transformers datasets -q
+# pip install streamlit
+
+import os
+import openai
+
+# open_ai_key_file = "openai_api_key_llm_2023.txt"
+# with open(open_ai_key_file, "r") as f:
+#   for line in f:
+#     OPENAI_KEY = line
+#     break
+
+from dotenv import load_dotenv, find_dotenv
+_ = load_dotenv(find_dotenv())
+
+# Read 100 flower names from 100flowers.txt
+# openai.api_key  = OPENAI_KEY
+file1 = open('./100flowers.txt', 'r')
+Lines = file1.readlines()
+Lines = [line.strip() for line in Lines]
+
+from openai import OpenAI
+from PIL import Image
+import urllib.request
+from io import BytesIO
+from IPython.display import display
+
+# client = OpenAI(api_key=OPENAI_KEY)
+
+# Code to generate images from names in 100flowers.txt
+# for prompt in Lines:
+#   response = client.images.generate(
+#     model="dall-e-3",
+#     prompt=prompt,
+#     size="1024x1024",
+#     quality="standard",
+#     n=1,
+#   )
+
+# Code to save generated images as png in Flowers folder
+#   image_url = response.data[0].url
+#   with urllib.request.urlopen(image_url) as image_url:
+#       img = Image.open(BytesIO(image_url.read()))
+
+#   img.save(f'./Flowers/{prompt}.png')
+
+
+# from transformers.utils import send_example_telemetry
+
+# send_example_telemetry("image_similarity_notebook", framework="pytorch")
+
+
+# Creates a list of flower names
+directory = './Flowers'
+png_files = [file[:-len('.png')].strip() for file in os.listdir(directory) if file.endswith(".png")]
+
+
+from datasets import Dataset, Image
+
+# Gets list of file paths
+def get_paths_to_images(images_directory):
+
+  paths = []
+  for file in os.listdir(images_directory):
+    print(file)
+    paths.append(file)
+
+  return paths
+
+# Creates dataset
+def load_dataset(images_directory):
+
+  paths_images = get_paths_to_images(images_directory)
+  print(paths_images[0])
+  dataset = Dataset.from_dict({"image": paths_images})
+
+  return dataset
+
+path_images = "./Flowers"
+dataset = load_dataset(path_images)
+
+from transformers import AutoFeatureExtractor, AutoModel
+
+model_ckpt = "jafdxc/vit-base-patch16-224-finetuned-flower"
+extractor = AutoFeatureExtractor.from_pretrained(model_ckpt)
+model = AutoModel.from_pretrained(model_ckpt)
+
+import torchvision.transforms as T
+import torch
+from PIL import Image
+
+
+# Data transformation chain.
+transformation_chain = T.Compose(
+    [
+        # We first resize the input image to 256x256 and then we take center crop.
+        T.Resize(int((256 / 224) * extractor.size["height"])),
+        T.CenterCrop(extractor.size["height"]),
+        T.ToTensor(),
+        T.Normalize(mean=extractor.image_mean, std=extractor.image_std),
+    ]
+)
+def extract_embeddings(model: torch.nn.Module):
+    """Utility to compute embeddings."""
+    device = model.device
+
+    def pp(batch):
+        images = batch["image"]
+        image_batch_transformed = torch.stack(
+            [transformation_chain(Image.open("./Flowers/" + image)) for image in images]
+        )
+        new_batch = {"pixel_values": image_batch_transformed.to(device)}
+        with torch.no_grad():
+            embeddings = model(**new_batch).last_hidden_state[:, 0].cpu()
+        return {"embeddings": embeddings}
+
+    return pp
+
+
+
+import numpy as np
+# Here, we map embedding extraction utility on our subset of candidate images.
+batch_size = 1
+device = "cuda" if torch.cuda.is_available() else "cpu"
+extract_fn = extract_embeddings(model.to(device))
+candidate_subset_emb = dataset.map(extract_fn, batched=True, batch_size=1)
+
+all_candidate_embeddings = np.array(candidate_subset_emb["embeddings"])
+all_candidate_embeddings = torch.from_numpy(all_candidate_embeddings)
+
+print(all_candidate_embeddings.shape[0])
+
+def compute_scores(emb_one, emb_two):
+    """Computes cosine similarity between two vectors."""
+    scores = torch.nn.functional.cosine_similarity(emb_one, emb_two)
+    return scores.numpy().tolist()
+
+
+def fetch_similar(image, top_k=5):
+    """Fetches the `top_k` similar images with `image` as the query."""
+    # Prepare the input query image for embedding computation.
+    image_transformed = transformation_chain(image).unsqueeze(0)
+    new_batch = {"pixel_values": image_transformed.to(device)}
+
+    # Compute the embedding.
+    with torch.no_grad():
+        query_embeddings = model(**new_batch).last_hidden_state[:, 0].cpu()
+
+    # Compute similarity scores with all the candidate images at one go.
+    # We also create a mapping between the candidate image identifiers
+    # and their similarity scores with the query image.
+    sim_scores = compute_scores(all_candidate_embeddings, query_embeddings)
+    similarity_mapping = dict(zip([str(index) for index in range(all_candidate_embeddings.shape[0])], sim_scores))
+
+    # Sort the mapping dictionary and return `top_k` candidates.
+    similarity_mapping_sorted = dict(
+        sorted(similarity_mapping.items(), key=lambda x: x[1], reverse=True)
+    )
+    id_entries = list(similarity_mapping_sorted.keys())[:top_k]
+
+    ids = list(map(lambda x: int(x.split("_")[0]), id_entries))
+    return ids
+
+import matplotlib.pyplot as plt
+
+
+def plot_images(images):
+   
+   for image, name in images:
+        if name == 'original':
+            count = 0
+            st.write("Showing the original image")
+            st.image (image, caption=name, width=None, use_column_width=None, clamp=False, channels='RGB', output_format='auto')
+
+        else:
+            count+=1
+            st.write(f"Showing similar image {count}")
+            img = Image.open(image)
+            st.image (img, caption=name, width=None, use_column_width=None, clamp=False, channels='RGB', output_format='auto')
+
+# Streamlit webpage code
+import streamlit as st
+from io import StringIO
+
+# Text Search
+st.title("Flower Type Demo")
+st.subheader("Upload an image of a Flower, you will get 5 flowers similar to it from our Dataset")
+
+upload_file = st.file_uploader('Upload a Flower Image')
+
+images = []
+
+if upload_file:
+    test_sample = Image.open(upload_file)
+
+    sim_ids = fetch_similar(test_sample)
+
+    for id in sim_ids:
+        images.append(("./Flowers/" + candidate_subset_emb[id]["image"],candidate_subset_emb[id]["image"]))
+
+
+    images.insert(0, (test_sample,'original'))
+    print(images)
+    plot_images(images)
+    st.write("")
\ No newline at end of file