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README.md CHANGED
@@ -1,12 +1,5 @@
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- ---
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- title: Ev Performance Demo
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- emoji: 🐢
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- colorFrom: yellow
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- colorTo: yellow
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- sdk: gradio
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- sdk_version: 6.3.0
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- app_file: app.py
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- pinned: false
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- ---
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- Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ # 🔋 Electric Vehicle Performance Prediction Model
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+
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+ ## 👨‍🎓 Author
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+ Student Research Project – Academic Year 2024–2025
app.py ADDED
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+ import gradio as gr
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+ import numpy as np
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+ import joblib
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+
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+ # =========================
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+ # Load model
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+ # =========================
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+ model = joblib.load("model.joblib")
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+
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+ # =========================
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+ # Prediction function
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+ # =========================
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+ def predict_ev(year, make, model_code, ev_type, cafv, utility):
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+ X = np.array([[year, make, model_code, ev_type, cafv, utility]])
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+ prediction = model.predict(X)
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+ return f"🔍 Electric Range dự đoán: {prediction[0]:.2f} km"
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+
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+ # =========================
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+ # Gradio Interface
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+ # =========================
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+ with gr.Blocks(title="EV Performance Prediction") as demo:
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+ gr.Markdown(
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+ """
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+ # 🔋 Electric Vehicle Performance Prediction
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+ **Dự báo hiệu suất kỹ thuật xe điện (Electric Range)**
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+ ---
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+ """
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+ )
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+
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+ gr.Markdown("### 📥 Nhập thông tin xe")
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+
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+ with gr.Row():
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+ year = gr.Number(label="Model Year", value=2020)
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+ make = gr.Number(label="Make (encoded)", value=10)
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+ model_code = gr.Number(label="Model (encoded)", value=20)
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+
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+ with gr.Row():
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+ ev_type = gr.Number(label="EV Type (encoded)", value=1)
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+ cafv = gr.Number(label="CAFV Eligibility (encoded)", value=0)
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+ utility = gr.Number(label="Electric Utility (encoded)", value=60)
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+
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+ predict_btn = gr.Button("🚀 Dự báo hiệu suất")
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+ output = gr.Textbox(label="Kết quả dự báo")
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+
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+ predict_btn.click(
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+ fn=predict_ev,
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+ inputs=[year, make, model_code, ev_type, cafv, utility],
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+ outputs=output
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+ )
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+
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+ gr.Markdown(
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+ """
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+ ---
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+ *Student Research Project – Academic Year 2024–2025*
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+ """
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+ )
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+
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+ demo.launch()
ev_model/README.md ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
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+
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+ # 🔋 Electric Vehicle Performance Prediction Model
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+
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+ ## 👨‍🎓 Author
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+ Student Research Project – Academic Year 2024–2025
ev_model/app.py ADDED
@@ -0,0 +1,58 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ import gradio as gr
2
+ import numpy as np
3
+ import joblib
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+
5
+ # =========================
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+ # Load model
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+ # =========================
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+ model = joblib.load("model.joblib")
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+
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+ # =========================
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+ # Prediction function
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+ # =========================
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+ def predict_ev(year, make, model_code, ev_type, cafv, utility):
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+ X = np.array([[year, make, model_code, ev_type, cafv, utility]])
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+ prediction = model.predict(X)
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+ return f"🔍 Electric Range dự đoán: {prediction[0]:.2f} km"
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+
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+ # =========================
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+ # Gradio Interface
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+ # =========================
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+ with gr.Blocks(title="EV Performance Prediction") as demo:
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+ gr.Markdown(
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+ """
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+ # 🔋 Electric Vehicle Performance Prediction
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+ **Dự báo hiệu suất kỹ thuật xe điện (Electric Range)**
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+ ---
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+ """
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+ )
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+
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+ gr.Markdown("### 📥 Nhập thông tin xe")
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+
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+ with gr.Row():
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+ year = gr.Number(label="Model Year", value=2020)
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+ make = gr.Number(label="Make (encoded)", value=10)
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+ model_code = gr.Number(label="Model (encoded)", value=20)
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+
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+ with gr.Row():
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+ ev_type = gr.Number(label="EV Type (encoded)", value=1)
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+ cafv = gr.Number(label="CAFV Eligibility (encoded)", value=0)
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+ utility = gr.Number(label="Electric Utility (encoded)", value=60)
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+
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+ predict_btn = gr.Button("🚀 Dự báo hiệu suất")
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+ output = gr.Textbox(label="Kết quả dự báo")
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+
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+ predict_btn.click(
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+ fn=predict_ev,
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+ inputs=[year, make, model_code, ev_type, cafv, utility],
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+ outputs=output
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+ )
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+
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+ gr.Markdown(
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+ """
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+ ---
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+ *Student Research Project – Academic Year 2024–2025*
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+ """
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+ )
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+
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+ demo.launch()
ev_model/model.joblib ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:2bb47892592702dc88f2ae782402df93cc4f3ae36b83cc42647262756474e63f
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+ size 70445
ev_model/requirements.txt ADDED
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+ scikit-learn
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+ xgboost
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+ joblib
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+ numpy
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+ gardio
model.joblib ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:2bb47892592702dc88f2ae782402df93cc4f3ae36b83cc42647262756474e63f
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+ size 70445
requirements.txt ADDED
@@ -0,0 +1,5 @@
 
 
 
 
 
 
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+ scikit-learn
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+ xgboost
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+ joblib
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+ numpy
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+ gardio