Create imageSearching.py

imageSearching.py

@@ -1,105 +0,0 @@
-import gradio as gr
-import torch
-import numpy as np
-import h5py
-import faiss
-import json
-import hydra
-import time
-import random
-from PIL import Image
-import io 
-import pickle
-
-def get_image(file, dataset_image_mask, processid_to_index, idx):
-    # idx = processid_to_index[query_id]
-    image_enc_padded = file["image"][idx].astype(np.uint8)
-    enc_length = dataset_image_mask[idx]
-    image_enc = image_enc_padded[:enc_length]
-    image = Image.open(io.BytesIO(image_enc))
-    return image
-
-def searchEmbeddings(id):
-    # get embeddings from file
-    embeddings_file = h5py.File('5m/extracted_features_of_all_keys.hdf5', 'r')
-
-    # variable and index initialization
-    dim = 768
-    count = 0
-    num_neighbors = 10
-
-    image_index = faiss.IndexFlatIP(dim)
-
-    # load dictionaries
-    with open("id_emb_dict.pickle", "rb") as f:
-        id_to_emb_dict = pickle.load(f)
-    with open("indx_to_id.pickle", "rb") as f:
-        indx_to_id_dict = pickle.load(f)
-
-    # get index
-    image_index = faiss.read_index("image_index.index")
-
-    # search for query
-    query = id_to_emb_dict[id]
-    query = query.astype(np.float32)
-    D, I = image_index.search(query, num_neighbors)
-
-    id_list = []
-    # need to convert I to id
-    i = 1
-    for indx in I[0]:
-        id = indx_to_id_dict[indx]
-        id_list.append(id)
-        # id_list.append(str(i) + ": " + id)
-        # i += 1
-
-    # get image data
-    dataset_hdf5_all_key = h5py.File('full5m/BIOSCAN_5M.hdf5', "r", libver="latest")['all_keys']
-    dataset_processid_list = [item.decode("utf-8") for item in dataset_hdf5_all_key["processid"][:]]
-    dataset_image_mask = dataset_hdf5_all_key["image_mask"][:]
-    processid_to_index = {pid: idx for idx, pid in enumerate(dataset_processid_list)}
-
-    image1 = get_image(dataset_hdf5_all_key, dataset_image_mask, processid_to_index, I[0][0])
-    image2 = get_image(dataset_hdf5_all_key, dataset_image_mask, processid_to_index, I[0][1])
-    image3 = get_image(dataset_hdf5_all_key, dataset_image_mask, processid_to_index, I[0][2])
-    image4 = get_image(dataset_hdf5_all_key, dataset_image_mask, processid_to_index, I[0][3])
-    image5 = get_image(dataset_hdf5_all_key, dataset_image_mask, processid_to_index, I[0][4])
-    image6 = get_image(dataset_hdf5_all_key, dataset_image_mask, processid_to_index, I[0][5])
-    image7 = get_image(dataset_hdf5_all_key, dataset_image_mask, processid_to_index, I[0][6])
-    image8 = get_image(dataset_hdf5_all_key, dataset_image_mask, processid_to_index, I[0][7])
-    image9 = get_image(dataset_hdf5_all_key, dataset_image_mask, processid_to_index, I[0][8])
-    image10 = get_image(dataset_hdf5_all_key, dataset_image_mask, processid_to_index, I[0][9])
-
-    # return id_list, id_list[0], id_list[1], id_list[2], id_list[3], id_list[4], id_list[5], id_list[6], id_list[7], id_list[8], id_list[9], image1, image2, image3, image4, image5, image6, image7, image8, image9, image10
-    # return id_list, indx_to_id_dict[I[0][0]], indx_to_id_dict[I[0][1]], indx_to_id_dict[I[0][2]], indx_to_id_dict[I[0][3]], indx_to_id_dict[I[0][4]], indx_to_id_dict[I[0][5]], indx_to_id_dict[I[0][6]], indx_to_id_dict[I[0][7]], indx_to_id_dict[I[0][8]], indx_to_id_dict[I[0][9]]
-    return id_list, image1, image2, image3, image4, image5, image6, image7, image8, image9, image10
-
-with gr.Blocks() as demo:
-    with gr.Column():
-        process_id = gr.Textbox(label="ID:", info="Enter a sample ID to search for")
-        process_id_list = gr.Textbox(label="Closest 10 matches:" )
-        search_btn = gr.Button("Search") 
-
-    with gr.Row():
-        image1 = gr.Image(label=1)
-        image2 = gr.Image(label=2)
-        image3 = gr.Image(label=3)
-        image4 = gr.Image(label=4)
-        image5 = gr.Image(label=5)
-    with gr.Row():
-        image6 = gr.Image(label=6)
-        image7 = gr.Image(label=7)
-        image8 = gr.Image(label=8)
-        image9 = gr.Image(label=9)
-        image10 = gr.Image(label=10)
-    
-    search_btn.click(fn=searchEmbeddings, inputs=process_id, 
-                     outputs=[process_id_list, image1, image2, image3, image4, image5, image6, image7, image8, image9, image10])
-
-
-# cant make functions with Image's as inputs
-# MUST be a way to format after
-
-
-# ARONZ671-20
-demo.launch(share=True)