app.py

import os
import streamlit as st
import pandas as pd
import numpy as np
import huggingface_hub as hfh
import requests

os.makedirs("labels", exist_ok=True)

voters = [
    "osman",
    "eren",
    "robin",
    "mira",
    "bilal",
    "volunteer-1",
    "volunteer-2",
    "volunteer-3",
    "volunteer-4",
    "volunteer-5",
]

api = hfh.HfApi(token=os.environ.get("hf_token"))


def get_list_of_images():
    files = api.list_repo_tree(repo_id="aifred-smart-life-coach/capstone-images", repo_type="dataset", recursive=True,)
    files = [file.path for file in files if file.path.endswith((".png", ".jpg"))]
    return files


def get_one_from_queue(voter: str):
    # get an image for the voter or return False if no image is left
    # aifred-smart-life-coach/labels labels dataset
    # labels dataset multiple csv files named as [voter name].csv
    # each csv file has the image image path vote date, votes
    url = f"https://huggingface.co/datasets/aifred-smart-life-coach/labels/raw/main/{voter}.csv"

    # fetch file and save it to the labels folder
    file_path = f"labels/{voter}.csv"
    req = requests.get(url)
    with open(file_path, "wb") as file:
        file.write(req.content)

    df = pd.read_csv(file_path)
    print(df)
    num_past_votes = df.shape[0]
    print("num_past_votes", num_past_votes)

    list_of_images = get_list_of_images()
    print("list_of_images", len(list_of_images))

    # get the list of images that are not present in the csv file
    images_not_voted = list(set(list_of_images) - set(df["image_path"].tolist()))
    print("images_not_voted", len(images_not_voted))

    return {"image": images_not_voted[0]} if images_not_voted else False


def update_vote(
    voter: str,
    image: str,
    healthiness: int,
    fat_level: int,
    muscle_level: int,
):
    url = f"https://huggingface.co/datasets/aifred-smart-life-coach/labels/raw/main/{voter}.csv"

    # fetch file and save it to the labels folder
    file_path = f"labels/{voter}.csv"
    req = requests.get(url)
    with open(file_path, "wb") as file:
        file.write(req.content)

    df = pd.read_csv(file_path)
    print(df)
    num_past_votes = df.shape[0]
    print("num_past_votes", num_past_votes)

    # get the list of images that are not present in the csv file
    images_not_voted = list(set(list_of_images) - set(df["image_path"].tolist()))
    print("images_not_voted", len(images_not_voted))

    # update the csv file with the new vote
    new_row = {
        "image_path": image,
        "healthiness": healthiness,
        "fat_level": fat_level,
        "muscle_level": muscle_level,
    }
    df = df.append(new_row, ignore_index=True)
    df.to_csv(file_path, index=False)

    # push the file to the dataset
    api.push_to_hub(file_path, repo_id="aifred-smart-life-coach/labels", repo_type="dataset", commit_message=f"Voted for {image}")

print(get_one_from_queue("osman"))





# login page
with st.form("login"):
    username = st.selectbox("Select voter", voters)
    password = st.text_input("Password (get password from [email protected])", type="password")
    submitted = st.form_submit_button("Login")


if submitted:
    if not password == os.environ.get("app_password"):
        st.error("The password you entered is incorrect")
        st.stop()
    else:
        st.success("Welcome, " + username)
        st.write("You are now logged in")

    with st.form("images"):
        image_path = get_one_from_queue(username)
        if not image_path:
            st.write("You have voted for all the images")
            st.stop()
        # https://huggingface.co/datasets/aifred-smart-life-coach/capstone-images/resolve/main/kaggle-human-segmentation-dataset/Women%20I/img/woman_image_200.jpg
        print(image_path)
        image_url = f"https://huggingface.co/datasets/aifred-smart-life-coach/capstone-images/resolve/main/{image_path}"
        print(image_url)
        st.image(image_url, width=300)
        gender = st.selectbox("Gender", [
            "Male",
            "Female",
            "Non-defining",
        ])
        healthiness = st.slider("How healthy is this picture?", 0, 100, 50)
        fat_level = st.slider("How fat is this picture?", 0, 100, 50)
        muscle_level = st.slider("How muscular is this picture?", 0, 100, 50)
        # Every form must have a submit button.
        submitted_second = st.form_submit_button("Submit")


    if submitted_second:
        update_vote(username, image_path, healthiness, fat_level, muscle_level)
        st.write("Vote submitted")
        # push the data to the database

    st.write("Outside the form")