RogerKoala/gen1-pokemon-classifier

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Model Summary

• Architecture: DenseNet121.
• Accuracy: 96% on the test set.
• Framework: Tensorflow.

Usage

import keras
from keras.src.utils import load_img
from keras.src.applications.densenet import preprocess_input
import numpy as np

pokedex = keras.saving.load_model("pokedex.keras")

image = load_img('image.png', target_size=(224, 224))

x = keras.utils.img_to_array(image)
x = np.expand_dims(x, axis=0)
x = preprocess_input(x)

preds = pokedex.predict(x)

# Important: You must ensure that the Pokémon are ordered alphabetically, as the model was trained using this sequence. You can obtain the .txt file from the following link: https://huggingface.co/spaces/RogerKoala/Pokedex/blob/main/Pokemons.txt

with open('Pokemons.txt', 'r') as f:
  class_labels = f.read().splitlines()

top_indices = preds[0].argsort()[-3:][::-1] 

for i in top_indices:
    print(f"{class_labels[i]}: {preds[0][i]*100:.2f}%")

System

• Input reqs: 224×224×3 RGB, normalized.

• Downstream deps: Class index→Pokémon metadata lookup.

Implementation requirements

• Training: T4 Google Colab.
• Duration: 1 hour and 15 minutes.

Model Characteristics

Model initialization

• Fine-tuned from ImageNet DenseNet121.

Model stats

Layer (type)	Output Shape	Param #
densenet121 (Functional)	(None, 7, 7, 1024)	7,037,504
global_average_pooling2d (GlobalAveragePooling2D)	(None, 1024)	0
dense (Dense)	(None, 128)	131,200
dropout (Dropout)	(None, 128)	0
dense_1 (Dense)	(None, 151)	19,479

Total params: 21,397,255 (81.62 MB)
Trainable params: 7,104,535 (27.10 MB)
Non-trainable params: 83,648 (326.75 KB)
Optimizer params: 14,209,072 (54.20 MB)

Training data

• Collected via scripts from public archives.

• Pre-processing: resize to 224×224, normalize.

Evaluation data

• Train: 2249 images.
• Test: 840 images.

Evaluation Results

Summary

Test accuracy: 96%

Usage limitations

• Only original 151.

• Fails on non-canonical art styles, low light, occlusion.

Google Colab Notebook

Explore the model training and inference workflow in this interactive notebook:

• Pokédex Colab Notebook

Demo

Visit the live Space to try it out:

• Hugging Face Space