Spaces:
Build error
Build error
File size: 1,575 Bytes
101ec35 beaf59e f312a7b beaf59e 101ec35 5ec5751 101ec35 5ec5751 8cc2f16 5ec5751 8cc2f16 5ec5751 0d524f5 5ec5751 519b727 5ec5751 beaf59e 5ec5751 beaf59e 5ec5751 8cc2f16 13124d8 beaf59e 13124d8 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 |
from PIL import Image
import tempfile
import gradio as gr
# Resto do código aqui...
def preprocess_image(image):
temp_file = tempfile.NamedTemporaryFile(suffix=".png", delete=False)
temp_file.write(image.read())
temp_file.close()
return temp_file.name
def classify_image(image_path, model_name):
model_config = next(m for m in models if m["name"] == model_name)
model = tf.keras.models.load_model(model_name)
image = Image.open(image_path).convert("RGB")
image = image.resize((model_config["size"], model_config["size"]))
image = np.array(image) / 255.0
input_image = np.expand_dims(image, axis=0)
prediction = model.predict(input_image).flatten()
if len(prediction) > 1:
probability = 100 * np.exp(prediction[0]) / (np.exp(prediction[0]) + np.exp(prediction[1]))
else:
probability = round(100. / (1 + np.exp(-prediction[0])), 2)
if probability > 45:
label = "Glaucoma"
elif probability > 25:
label = "Unclear"
else:
label = "Not glaucoma"
return label, probability
inputs = [
gr.inputs.Image(label="Eye image"),
gr.inputs.Dropdown(choices=[m["name"] for m in models], label="Model"),
]
outputs = [
gr.outputs.Textbox(label="Predicted label"),
gr.outputs.Textbox(label="Probability of glaucoma (0-100)"),
]
examples = [
[preprocess_image(open("example_image.jpg", "rb")), "my_model.h5"],
[preprocess_image(open("example_image_2.jpg", "rb")), "my_model_2.h5"]
]
gr.Interface(classify_image, inputs, outputs, examples=examples).launch()
|