How to calculate image similarity of given 2 images by using open AI Clip model - which method / AI model is best for calculating image similarity?

I have prepared a small example code but It is throwing error. Can't solve the problem because it is supposed to work.

Also do you think are there any better approaches to calculate image similarity? I want to find similar cloth images. e.g. I will give an image of a coat and I want to find similar coats.

also would this code handle all dimensions of images and all types of images?

here the code

import torch
import torchvision.transforms as transforms
import urllib.request
from transformers import CLIPProcessor, CLIPModel, CLIPTokenizer
from PIL import Image

# Load the CLIP model
device = "cuda" if torch.cuda.is_available() else "cpu"
model_ID = "openai/clip-vit-base-patch32"
model = CLIPModel.from_pretrained(model_ID).to(device)

preprocess = CLIPProcessor.from_pretrained(model_ID)


# Define a function to load an image and preprocess it for CLIP
def load_and_preprocess_image(image_path):
    # Load the image from the specified path
    image = Image.open(image_path)

    # Apply the CLIP preprocessing to the image
    image = preprocess(image).unsqueeze(0).to(device)

    # Return the preprocessed image
    return image

# Load the two images and preprocess them for CLIP
image_a = load_and_preprocess_image('/content/a.png')
image_b = load_and_preprocess_image('/content/b.png')

# Calculate the embeddings for the images using the CLIP model
with torch.no_grad():
    embedding_a = model.encode_image(image_a)
    embedding_b = model.encode_image(image_b)

# Calculate the cosine similarity between the embeddings
similarity_score = torch.nn.functional.cosine_similarity(embedding_a, embedding_b)

# Print the similarity score
print('Similarity score:', similarity_score.item())

here the error message

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
[<ipython-input-24-e95a926e1bc8>](https://localhost:8080/#) in <module>
     25 
     26 # Load the two images and preprocess them for CLIP
---> 27 image_a = load_and_preprocess_image('/content/a.png')
     28 image_b = load_and_preprocess_image('/content/b.png')
     29 

3 frames
[/usr/local/lib/python3.9/dist-packages/transformers/tokenization_utils_base.py](https://localhost:8080/#) in _call_one(self, text, text_pair, add_special_tokens, padding, truncation, max_length, stride, is_split_into_words, pad_to_multiple_of, return_tensors, return_token_type_ids, return_attention_mask, return_overflowing_tokens, return_special_tokens_mask, return_offsets_mapping, return_length, verbose, **kwargs)
   2579 
   2580         if not _is_valid_text_input(text):
-> 2581             raise ValueError(
   2582                 "text input must of type `str` (single example), `List[str]` (batch or single pretokenized example) "
   2583                 "or `List[List[str]]` (batch of pretokenized examples)."

ValueError: text input must of type `str` (single example), `List[str]` (batch or single pretokenized example) or `List[List[str]]` (batch of pretokenized examples)

source https://stackoverflow.com/questions/75709193/how-to-calculate-image-similarity-of-given-2-images-by-using-open-ai-clip-model

Why is my reports service not connecting?

I am trying to pull some data from a Postgres database using Node.js and node-postures but I can't figure out why my service isn't connecting. my routes/index.js file: const express = require('express'); const router = express.Router(); const ordersCountController = require('../controllers/ordersCountController'); const ordersController = require('../controllers/ordersController'); const weeklyReportsController = require('../controllers/weeklyReportsController'); router.get('/orders_count', ordersCountController); router.get('/orders', ordersController); router.get('/weekly_reports', weeklyReportsController); module.exports = router; My controllers/weeklyReportsController.js file: const weeklyReportsService = require('../services/weeklyReportsService'); const weeklyReportsController = async (req, res) => { try { const data = await weeklyReportsService; res.json({data}) console...

How to show number of registered users in Laravel based on usertype?

i'm trying to display data from the database in the admin dashboard i used this: <?php use Illuminate\Support\Facades\DB; $users = DB::table('users')->count(); echo $users; ?> and i have successfully get the correct data from the database but what if i want to display a specific data for example in this user table there is "usertype" that specify if the user is normal user or admin i want to user the same code above but to display a specific usertype i tried this: <?php use Illuminate\Support\Facades\DB; $users = DB::table('users')->count()->WHERE usertype =admin; echo $users; ?> but it didn't work, what am i doing wrong? source https://stackoverflow.com/questions/68199726/how-to-show-number-of-registered-users-in-laravel-based-on-usertype

The number of nodes and edges I calculated manually and by a method provided by networkx library dont match

I am trying to analyse a graph using networkx library in Python. I have implemented a function that returns the nodes and edges of that graph. After that I counted the number of nodes and edges by implementing the len() function for nodes and edges, which gave me 17 for both nodes and edges. However, when I used the method graph.number_of_nodes() of networkx library it gave me 53. My code: import pandas as pd import networkx as nx import matplotlib.pyplot as plt header_list = ["a","b","w"] E =pd.read_csv("aves-barn-swallow-contact-network.edges",sep=" ",header= None,names=header_list) # print(E.head()) # prints first few rows of the csv file G = nx.from_pandas_edgelist(E,"a","b",["w"]) nx.draw(G) plt.show() class GraphAnalyse: #finding nodes and edges def nodeEdge(self,Graph): nodes = Graph.nodes() edges = Graph.edges() ...

StacksPedia

Search This Blog