app.py

import os
import clip
import torch
import logging
import json
import pickle
import gradio as gr


logger = logging.getLogger("basebody")
CLIP_MODEL_NAME = "ViT-B/16"

TEXT_PROMPTS_FILE_NAME = "text_prompts.json"
LOGISTIC_REGRESSION_MODEL_FILE_NAME = "logistic_regression_l1_oct_2.pkl"


clip_model, preprocess = clip.load(CLIP_MODEL_NAME, device="cpu")

with open(
    os.path.join(os.path.dirname(__file__), TEXT_PROMPTS_FILE_NAME), "r"
) as f:
    text_prompts = json.load(f)
with open(
    os.path.join(
        os.path.dirname(__file__), LOGISTIC_REGRESSION_MODEL_FILE_NAME
    ),
    "rb",
) as f:
    lr_model = pickle.load(f)


def greet(name):
    return "Hello " + name + "!"


iface = gr.Interface(
    fn=greet,
    inputs="image",
    outputs="text",
    allow_flagging="manual"
)
iface.launch()