public & private lb

Makefile

@@ -0,0 +1,10 @@
+.PHONY: quality style
+
+quality:
+	python -m black --check --line-length 119 --target-version py38 .
+	python -m isort --check-only .
+	python -m flake8 --max-line-length 119
+
+style:
+	python -m black --line-length 119 --target-version py38 .
+	python -m isort .

Overview.py

@@ -10,7 +10,8 @@ st.write("# Welcome to Cats vs Dogs! 👋")
 st.markdown(
     """
     In this competition, you will be creating an image classifier that can distinguish between cats and dogs.
-    You can use any model you want, but we recommend using a pretrained model from the [🤗 Hub](https://huggingface.co/models).
+    You can use any model you want, but we recommend using a pretrained model from the
+    [🤗 Hub](https://huggingface.co/models).
 
     Rules:
     - You can make upto 5 submissions per day.
@@ -19,7 +20,8 @@ st.markdown(
     - Your final score will be based on your private split performance.
     - The final rankings will be based on the private split performance.
     - No cheating! You can only use the test data for inference. You cannot use it to train your model.
-    - No private sharing of code or data. You can discuss the competition on the forums, but please do not share any code or data.
+    - No private sharing of code or data. You can discuss the competition on the forums, but please do not share any
+    code or data.
     - Have fun! 🤗
 
     For detailed rules, please check the [rules page](https://huggingface.co/competitions/transformers-cats-vs-dogs).

config.py

@@ -1,7 +1,9 @@
 import os
-from dotenv import load_dotenv
+from datetime import datetime
 from pathlib import Path
 
+from dotenv import load_dotenv
+
 if Path(".env").is_file():
     load_dotenv(".env")
 
@@ -14,3 +16,6 @@ AUTOTRAIN_TOKEN = os.getenv("AUTOTRAIN_TOKEN")
 HF_ACCESS_TOKEN = os.getenv("HF_ACCESS_TOKEN")
 AUTOTRAIN_BACKEND_API = os.getenv("AUTOTRAIN_BACKEND_API")
 SUBMISSION_LIMIT = int(os.getenv("SUBMISSION_LIMIT"))
+SELECTION_LIMIT = int(os.getenv("SELECTION_LIMIT"))
+END_DATE = os.getenv("END_DATE")
+END_DATE = datetime.strptime(END_DATE, "%Y-%m-%d")

pages/1_🤗_Dataset.py

@@ -1,6 +1,4 @@
 import streamlit as st
-import time
-import numpy as np
 
 
 def app():

pages/2_📝_Leaderboard.py

@@ -1,5 +1,5 @@
-import streamlit as st
 import pandas as pd
+import streamlit as st
 
 
 def fetch_leaderboard():

pages/3_🔥_New Submission.py

@@ -1,10 +1,10 @@
-import streamlit as st
-from huggingface_hub import HfApi, CommitOperationAdd
 import uuid
-import os
-import pandas as pd
-import utils
+
+import streamlit as st
+from huggingface_hub import HfApi
+
 import config
+import utils
 
 SUBMISSION_TEXT = """You can make upto 5 submissions per day.
 The test data has been divided into public and private splits.

pages/4_⭐️_Submission History.py

@@ -1,15 +1,32 @@
-import streamlit as st
-from huggingface_hub import HfApi, CommitOperationAdd
-import uuid
-import os
+from datetime import datetime
+
 import pandas as pd
-import utils
+import streamlit as st
+
 import config
+import utils
 
 SUBMISSION_TEXT = """You can select upto 2 submissions for private leaderboard.
 """
 
 
+def get_subs(user_info, private=False):
+    # get user submissions
+    user_id = user_info["id"]
+    user_submissions = utils.fetch_submissions(user_id)
+    submissions_df = pd.DataFrame(user_submissions)
+    if not private:
+        submissions_df = submissions_df.drop(columns=["private_score"])
+        submissions_df = submissions_df[
+            ["date", "submission_id", "public_score", "submission_comment", "selected", "status"]
+        ]
+    else:
+        submissions_df = submissions_df[
+            ["date", "submission_id", "public_score", "private_score", "submission_comment", "selected", "status"]
+        ]
+    return submissions_df
+
+
 def app():
     st.set_page_config(page_title="Submission History", page_icon="🤗")
     st.write("## Your Submissions")
@@ -27,11 +44,23 @@ def app():
             st.error("Please verify your email on Hugging Face Hub")
             return
 
-        # get user submissions
-        user_id = user_info["id"]
-        user_submissions = utils.fetch_submissions(user_id)
-        submissions_df = pd.DataFrame(user_submissions)
-        st.write(submissions_df)
+        public_lb, private_lb = st.tabs(["Public", "Private"])
+        current_date_time = datetime.now()
+        print(current_date_time)
+        print(config.END_DATE)
+        print(current_date_time >= config.END_DATE)
+        with public_lb:
+            st.header("Public Leaderboard")
+            submission_df = get_subs(user_info, private=False)
+            st.write(submission_df)
+
+        with private_lb:
+            if current_date_time >= config.END_DATE:
+                st.header("Private Leaderboard")
+                submission_df = get_subs(user_info, private=True)
+                st.write(submission_df)
+            else:
+                st.error("Private Leaderboard will be available after the competition ends")
 
 
 if __name__ == "__main__":

utils.py

@@ -1,12 +1,14 @@
+import datetime
+import io
+import json
 import time
+
 import requests
-import config
 from huggingface_hub import HfApi, hf_hub_download
-import json
-import datetime
-import io
 from huggingface_hub.utils._errors import EntryNotFoundError
 
+import config
+
 
 def get_auth_headers(token: str, prefix: str = "Bearer"):
     return {"Authorization": f"{prefix} {token}"}
@@ -199,12 +201,16 @@ def increment_submissions(user_id, submission_id, submission_comment):
     with open(user_fname, "r") as f:
         user_submission_info = json.load(f)
     todays_date = datetime.datetime.now().strftime("%Y-%m-%d")
+    # here goes all the default stuff for submission
     user_submission_info["submissions"].append(
         {
             "date": todays_date,
             "submission_id": submission_id,
             "submission_comment": submission_comment,
             "status": "pending",
+            "selected": False,
+            "public_score": -1,
+            "private_score": -1,
         }
     )
     # count the number of times user has submitted today