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import gradio as gr
from PIL import Image
from io import BytesIO
import PIL
import numpy as np
import os
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
def sentence_builder(age, sex, skin_type, allergies, diet, file):
import index
print(age, sex, skin_type, allergies, diet)
response = index.predict(file)
predictions = response['prediction']
prediction = np.array(predictions)
data = response
data["prediction"] = prediction
labels = ["Low", "Moderate", "Severe"]
show_prediction = np.zeros((4, 3))
for in_, pred in enumerate(prediction):
show_prediction[in_] = pred
output1 = {labels[i]: float(show_prediction[0][i]) for i in range(3)}
output2 = {labels[i]: float(show_prediction[1][i]) for i in range(3)}
output3 = {labels[i]: float(show_prediction[2][i]) for i in range(3)}
output4 = {labels[i]: float(show_prediction[3][i]) for i in range(3)}
data['age'] = age
data['gender'] = sex
data['skin_type'] = skin_type
data['allergies'] = allergies
data['diet'] = diet
try:
response = index.recommendation(data)
data = response.json()
content = data['choices'][0]['message']['content']
return content, output1, output2, output3, output4
except:
return "No recommendation found", output1, output2, output3, output4
with gr.Blocks() as demo:
gr.Markdown("Flip text or image files using this demo.")
with gr.Row():
with gr.Column():
age = gr.Number(value=20, label="Age")
sex = gr.Radio(["Male", "Female", "Other"], label="Gender", info="Your Gender")
skin_type = gr.CheckboxGroup(["Oily", "Dry", "Normal"], label="Skin", info="Skin Type")
allergy = gr.Dropdown(
["benzoyl peroxide", "salicylic acid", "Sun-exposure", "Itching", "Swelling", "Redness"],
multiselect=True, label="Allergies",
info="Tell us your allergies and symptoms"
)
diet = gr.CheckboxGroup(["Veg", "Non-Veg",], label="Diet", info="Select your diet preference")
img = gr.Image(source="upload", type="pil", label="Face Image (with open eye)")
submit = gr.Button("Submit")
with gr.Tab("Model:Severity Prediction"):
chin = gr.Label(num_top_classes=3, label="Chin|Acne Level")
fh = gr.Label(num_top_classes=3, label="Fore Head|Acne Level")
lc = gr.Label(num_top_classes=3, label="Left Cheek|Acne Level")
rc = gr.Label(num_top_classes=3, label="Right Cheek|Acne Level")
with gr.Tab("Recommendation:Treatment Plan"):
html_output = gr.HTML('Recommendation will be shown here')
submit.click(sentence_builder, inputs=[age, sex, skin_type, allergy, diet, img], outputs=[html_output, rc, lc, chin, fh])
if __name__ == "__main__":
demo.launch(server_name="0.0.0.0", server_port=7860) |