|
from transformers import ViTImageProcessor, ViTForImageClassification, AutoModelForImageClassification, AutoTokenizer, pipeline |
|
|
|
from PIL import Image |
|
import requests |
|
import os |
|
import gradio as gr |
|
from timeit import default_timer as timer |
|
from typing import Tuple, Dict |
|
import torch |
|
|
|
start_time = timer() |
|
|
|
|
|
|
|
image = Image.open('examples/00009.png') |
|
classifier = pipeline("image-classification", model="bazyl/gtsrb-model", tokenizer="bazyl/gtsrb-model") |
|
result = classifier(image) |
|
response = {result[i]["label"]: result[i]["score"] for i in range(len(result))} |
|
|
|
pred_time = round(timer() - start_time, 5) |
|
|
|
print(classifier(image), pred_time) |
