!git clone https://github.com/kingchloexx/CLIP-Image-Classification # if not in a notebook, run in console (w/o the "!")
import os
os.chdir("Image-Classification")

from classify import load, classify, encode

filename = "../input.jpg"

load_categories = "imagenet"

print("loading categories")
load(load_categories)

print("classifying")
print(classify(filename))

load("imagenet") #imagenet categories
load("pokemon") #loads a list of 721 pokemon names as categories
load("dog vs cat") #dog and cat as categories
load("emojis") #emojis :)
load(["banana", "elephant", "monkey"]) #any custom words in a list will do as well

classify(filename) #returns the highest scoring class
classify(filename, return_raw=True) #returns the scores for all the classes (cosine_similarity)

encode("input.jpg") #encode based on filename, it'll be detected if it ends w/ png, jpg, or jpeg
encode("an image of a flower") #encode based on text

import subprocess

CUDA_version = [s for s in subprocess.check_output(["nvcc", "--version"]).decode("UTF-8").split(", ") if s.startswith("release")][0].split(" ")[-1]
print("CUDA version:", CUDA_version)

if CUDA_version == "10.0":
    torch_version_suffix = "+cu100"
elif CUDA_version == "10.1":
    torch_version_suffix = "+cu101"
elif CUDA_version == "10.2":
    torch_version_suffix = ""
else:
    torch_version_suffix = "+cu110"
!git clone https://github.com/kingchloexx/CLIP-Image-Classification
! pip install torch==1.7.1{torch_version_suffix} torchvision==0.8.2{torch_version_suffix} -f https://download.pytorch.org/whl/torch_stable.html ftfy regex
!pip install ftfy