app_copy.py

import streamlit as st
import pandas as pd
import matplotlib.pyplot as plt

from datasets import load_dataset
dataset = load_dataset("rwcuffney/pick_a_card_test")

#tokenizer = AutoTokenizer.from_pretrained("bert-base-cased")
#tokenized_data = tokenizer(dataset["sentence"], return_tensors="np", padding=True)

from transformers import AutoFeatureExtractor, AutoModelForImageClassification
'''
extractor = AutoFeatureExtractor.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099221")
model = AutoModelForImageClassification.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099221")
st.write(model.__class__.__name__)
st.code(type(model))


extractor = AutoFeatureExtractor.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099222")
model = AutoModelForImageClassification.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099222")
st.write(model.__class__.__name__)
st.code(type(model))


extractor = AutoFeatureExtractor.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099223")
model = AutoModelForImageClassification.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099223")
st.write(model.__class__.__name__)
st.code(type(model))

'''

extractor = AutoFeatureExtractor.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099224")
model = AutoModelForImageClassification.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099224")
st.write(model.__class__.__name__)
st.code(type(model))

from transformers import AutoImageProcessor
import torch


image = dataset["test"][0]
st.image(image)

image_processor = AutoImageProcessor.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099224")
inputs = image_processor(image, return_tensors="pt")


'''
extractor = AutoFeatureExtractor.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099225")
model = AutoModelForImageClassification.from_pretrained("rwcuffney/autotrain-pick_a_card-3726099225")
st.write(model.__class__.__name__)
st.code(type(model))
'''


'''
x = st.slider('Select a value')
st.write(x, 'squared is', x * x)

import pandas as pd
#df = pd.read_csv('https://rwcuffney/autotrain-data-pick_a_card/cards.csv').sort_values('class index')
#st.dataframe(df.head(3))
# from datasets import load_dataset

dataset = load_dataset("https://rwcuffney/autotrain-data-pick_a_card")
# st.write(type(dataset))
# st.write('Hello World')

from datasets import load_dataset
#dataset = load_dataset("rwcuffney/autotrain-data-pick_a_card")
#st.write(dataset)

import pandas as pd
import requests
import io
    
# Downloading the csv file from your GitHub account
url = "https://huggingface.co./datasets/rwcuffney/autotrain-data-pick_a_card/raw/main/cards.csv" # Make sure the url is the raw version of the file on GitHub
download = requests.get(url).content


# Reading the downloaded content and turning it into a pandas dataframe
df = pd.read_csv(io.StringIO(download.decode('utf-8')))
#df = pd.read_csv('playing_cards/cards.csv').sort_values('class index')
df_test = df[df['data set']=='test']
df_train = df[df['data set']=='train']
df_validate = df[df['data set']=='validate']

from datasets import load_dataset #this isn't working
dataset = load_dataset("rwcuffney/pick_a_card_test") #rwcuffney/pick_a_card_test

st.write(df.head(20))
###
'''