Upload 3 files

app.py

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+import gradio as gr
+import pandas as pd
+import numpy as np
+import pickle
+import sklearn
+model = pickle.load(open('random_forest_regression_model.pkl', 'rb'))
+
+import gradio as gr
+def car(Year,owners,sp,fuel,distance,tyype,trans):
+  if fuel =="PETROL":
+    p,d=1,0
+  if fuel =="DIESEL":
+    p,d=0,1
+  if fuel =="CNG":
+    p,d=0,0
+  year = 2022-Year
+  if tyype=="Individual":
+    st=1
+  else:
+    st=0
+  if trans=="Manual":
+    t=1
+  else:
+    t=0
+  error = "【 𝗘𝗿𝗿𝗼𝗿 𝟰𝟬𝟰 : 𝗩𝗮𝗹𝘂𝗲 𝗠𝗶𝘀𝘀𝗶𝗻𝗴 】"
+  prediction=model.predict([[sp,distance,owners,year,d,p,st,t]])
+  output=round(prediction[0],2)
+  ou= str(output)
+  if Year==0 or distance==0 or sp==0:
+    return error
+  else:
+    return "The Price of Will be  ₹" + ou  + "L !"
+# face = gr.Interface(fn=start, inputs=["text", "checkbox","N", gr.inputs.Slider(0, 100),gr.inputs.Radio(["add", "subtract", "multiply"])], outputs=["text", "number"])
+# face.launch()
+ts= """ 
+Used Car  Price  Prediction"""
+# ---------------------------------INPUTS :------------------------------
+
+# in1=gr.inputs.Textbox(placeholder="En",label="MO")
+in2=gr.inputs.Number(label='Which Model (Year)【*】',default=0)
+in3= gr.inputs.Slider(0, 10,1,label="No. of Previous Owners eg.1,2,3")
+in4=gr.inputs.Number(label='Kilometeres Drived【*】',default=0)
+in5= gr.inputs.Radio(["PETROL", "DIESEL", "CNG"])
+in6=gr.inputs.Dropdown(["Individual", "Dealer"],label="You Are")
+in7=gr.inputs.Dropdown(["Automatic", "Manual"],label="Transmission Type")
+in8=gr.inputs.Number(label='Showroom Price ₹(in LAKHS)【*】',default=0)
+
+interface = gr.Interface(fn=car,
+                         inputs=[in2,in3,in8,in5,in4,in6,in7],
+                         outputs=["text"],title=ts,theme="peach",css="""
+                         .gradio_bg[theme=default] .gradio_interface .panel_button.submit {
+
+	background-color: rgba(99, 102, 241, var(--tw-bg-opacity));
+
+}
+.gradio_bg[theme=peach] .gradio_interface .panel_header {
+  font-family: Arial, Helvetica, sans-serif;;
+  font-size: 17px;
+}
+.gradio_page .title{
+  font-family: "Copperplate",Fantasy;
+  font-size: 47px;
+}"""
+                         )
+interface.launch(inline=False)

random_forest_regression_model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:24163318b89fd4aa73abd40d0b3e908fac12d6aa69adaa30098f5d769c993123
+size 16677984

requirements.txt

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+sklearn