Arigadam/img2float

Model description

A very simple model that converts an image into a number!

the hepler function

(requirements: numpy Pillow)

import numpy as np
from PIL import Image

def predict(model, img):
    pil_image = img
    pil_image = pil_image.resize((64, 64))

    image_array = np.array(pil_image) / 255.0

    image_array = np.expand_dims(image_array, axis=0)

    input_shape = (64, 64, pil_image.mode == 'RGB' and 3 or 1)

    decimal_prediction = model.predict(image_array)[0][0]
    return decimal_prediction

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

Hyperparameters	Value
name	Adam
weight_decay	None
clipnorm	None
global_clipnorm	None
clipvalue	None
use_ema	False
ema_momentum	0.99
ema_overwrite_frequency	None
jit_compile	False
is_legacy_optimizer	False
learning_rate	0.0010000000474974513
beta_1	0.9
beta_2	0.999
epsilon	1e-07
amsgrad	False
training_precision	float32

Model Plot

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