last push

app.py

@@ -2,37 +2,6 @@ from fastai.vision.all import *
 import gradio as gr
 
 # Define the list of 1st generation Pokémon class names
-"""class_names = [
-    "Bulbasaur", "Ivysaur", "Venusaur",
-    "Charmander", "Charmeleon", "Charizard",
-    "Squirtle", "Wartortle", "Blastoise",
-    "Caterpie", "Metapod", "Butterfree",
-    "Weedle", "Kakuna", "Beedrill",
-    "Pidgey", "Pidgeotto", "Pidgeot",
-    "Rattata", "Raticate", "Spearow",
-    "Fearow", "Ekans", "Arbok",
-    "Psyduck", "Golduck", "Machop",
-    "Machoke", "Machamp", "Bellsprout",
-    "Weepinbell", "Victreebel", "Tentacool",
-    "Tentacruel", "Geodude", "Graveler",
-    "Golem", "Ponyta", "Rapidash",
-    "Magnemite", "Magneton", "Krabby",
-    "Kingler", "Exeggcute", "Exeggutor",
-    "Cubone", "Marowak", "Hitmonlee",
-    "Hitmonchan", "Lickitung", "Koffing",
-    "Weezing", "Rhyhorn", "Rhydon",
-    "Chansey", "Tangela", "Kangaskhan",
-    "Horsea", "Seadra", "Goldeen",
-    "Seaking", "Staryu", "Starmie",
-    "Mr. Mime", "Scyther", "Jynx",
-    "Electabuzz", "Magmar", "Pinsir",
-    "Tauros", "Magikarp", "Gyarados",
-    "Lapras", "Ditto", "Eevee",
-    "Vaporeon", "Jolteon", "Flareon",
-    "Porygon", "Omanyte", "Omastar",
-    "Kabuto", "Kabutops", "Aerodactyl",
-    "Mew", "Mewtwo"
-]"""
 
 def get_x(item):
     return item['image']  # Access images directly
@@ -53,14 +22,11 @@ def classify_pokemon(img):
 
 # Gradio interface setup
 title = "Pokémon first gen classifier"
-description = "Based on the famous scene (Who's that Pokémon) of the pokemon tv show, this neural network accurately classifies a pokemon image."
+description = "Based on the famous scene (Who's that Pokémon) of the Pokémon TV show, this neural network accurately classifies a Pokémon image."
 image = gr.Image(type='pil')  # Image size should match your training data size (e.g., 128x128)
 label = gr.Label()
 examples =  ['zapdos.jpg']
 
-
-
-
 # Set up Gradio interface
 intf = gr.Interface(
     fn=classify_pokemon,