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import streamlit as st |
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import json |
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import pandas as pd |
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import numpy as np |
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st.set_page_config(page_title="PetSet", layout="centered") |
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st.markdown("<h1 style='text-align: center;'>🐾 PetSet – Your Dataset Pet</h1>", unsafe_allow_html=True) |
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st.markdown("<p style='text-align: center; font-size: 18px;'>Upload a LeRobot .json dataset and start caring for your pet!</p>", unsafe_allow_html=True) |
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uploaded_file = st.file_uploader("📂 Upload your LeRobotDataset (.json)", type=["json"]) |
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if uploaded_file: |
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data = json.load(uploaded_file) |
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episodes = data.get("episodes", []) |
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if not episodes: |
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st.error("No episodes found in this file.") |
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else: |
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df = pd.DataFrame(episodes) |
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st.success(f"{len(episodes)} episodes loaded successfully!") |
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success_rate = df["success"].mean() |
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duration_std = df["duration"].std() |
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health = 100 - df['success'].value_counts().get(False, 0) * 10 |
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energy = success_rate * 100 |
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attention = max(0, 100 - duration_std * 10) |
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col1, col2, col3 = st.columns(3) |
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with col1: |
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st.metric("❤️ Health", f"{int(health)}%") |
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with col2: |
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st.metric("⚡ Energy", f"{int(energy)}%") |
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with col3: |
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st.metric("🧠 Attention", f"{int(attention)}%") |
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st.markdown("---") |
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st.image("https://media.giphy.com/media/v1.Y2lkPTc5MGI3NjExZ2EyZWkyd2ZzMmFmd3FuNm1jY2Fjdm42a2p6dDh4cGc1dzNsb25uMSZlcD12MV9naWZzX3NlYXJjaCZjdD1n/VbnUQpnihPSIgIXuZv/giphy.gif", width=200, caption="Your Pet") |
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st.markdown("### 🛠 What would you like to do?") |
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col_a, col_b, col_c = st.columns(3) |
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with col_a: |
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feed = st.button("🍎 Feed Data") |
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with col_b: |
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heal = st.button("🩺 Heal Pet") |
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with col_c: |
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check = st.button("🧪 Check Quality") |
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if heal: |
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original_len = len(data["episodes"]) |
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data["episodes"] = [ep for ep in episodes if ep.get("success", True)] |
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removed = original_len - len(data["episodes"]) |
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st.success(f"Removed {removed} failed episodes.") |
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if check: |
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problems = df['success'].value_counts().get(False, 0) |
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st.markdown(f"<div style='padding: 15px; background-color: #fff3cd; border-radius: 10px;'><strong>⚠️ Found {problems} corrupted episodes!</strong></div>", unsafe_allow_html=True) |
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st.markdown("### 📦 Dataset Preview") |
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st.dataframe(df[["id", "success", "duration", "avg_accel"]]) |
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st.markdown("---") |
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if st.button("💾 Download Cleaned Dataset"): |
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cleaned_json = json.dumps(data, indent=2) |
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st.download_button("Download JSON", cleaned_json, file_name="cleaned_dataset.json") |
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else: |
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st.info("👆 Upload a dataset file to begin.") |
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