| import gradio as gr |
| import numpy as np |
| import tensorflow as tf |
|
|
| |
| model = tf.keras.models.load_model("cnn_model_v2.h5") |
|
|
|
|
| def predict(input_dict): |
| if not input_dict or "composite" not in input_dict: |
| return {str(i): 0.0 for i in range(10)} |
|
|
|
|
| image = input_dict["composite"] |
|
|
| MAX_INTENSITY_SUM = 343 |
| |
| |
| image = image[:, :, :3] |
|
|
| |
| image = tf.image.rgb_to_grayscale(image) |
|
|
| |
| image = tf.image.resize(image, [28, 28]) |
|
|
| |
| image = 255 - image |
| image = image / 255.0 |
| image = image.numpy().reshape(-1, 28, 28, 1) |
|
|
| if np.sum(image) > MAX_INTENSITY_SUM: |
| return "Please try Again" |
|
|
| |
| prediction = model.predict(image) |
| probs = tf.nn.softmax(prediction[0]).numpy() |
|
|
| if probs.max() < 0.5: |
| return "Please try again." |
| else: |
| return {str(i): float(probs[i]) for i in range(10)} |
|
|
| |
| sketchpad = gr.Sketchpad() |
| label = gr.Label(num_top_classes=3) |
|
|
| gr.Interface( |
| fn=predict, |
| inputs=sketchpad, |
| outputs=label, |
| title="MNIST Digit Sketch Pad", |
| description="Draw a digit (0–9) and this model will try to guess what number you wrote! It’s trained on the original MNIST dataset of handwritten digits.", |
| ).launch(debug = False) |
