BackEnd_ML_REST_Server/Flask_Server_App.py at main · AlwaysCare/BackEnd_ML_REST_Server · GitHub

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from flask import Flask, request, jsonify
from werkzeug.utils import secure_filename

import sys
sys.path.append("../../Model/yolov5/classify/")
sys.path.append("../../Model/yolov5/segment/")
import flask_server_predict
import flask_server_predict_seg

import os
import pathlib
from datetime import datetime
from collections import defaultdict


app = Flask(__name__)


# @app.route("/")
@app.route("/always-care/model/eye", methods=["POST"])
def eye_model():

    if request.method == "POST":

        save_path = "../client-request-log/"

        file = request.files["image_file"]
        type = request.form["image_type"]
        userId = request.form["userId"]

        save_path += str(userId)

        if pathlib.Path(save_path).exists() == False:
            os.mkdir(save_path)

        request_time = datetime.today().strftime("%Y%m%d%H%M%S")

        save_path += "/"
        save_path += request_time

        if pathlib.Path(save_path).exists() == False:
            os.mkdir(save_path)

        save_path += "/"
        save_path += secure_filename(file.filename)

        file.save(save_path)

        # print(file.filename)
        # print(info)

        res = prediction(type, save_path)

        if res == False:
            return False
        else:
            return res

    return False


@app.route("/always-care/model/skin", methods=["POST"])
def skin_model():

    if request.method == "POST":

        save_path = "../client-request-log/"

        file = request.files["image_file"]
        type = request.form["image_type"]
        userId = request.form["userId"]

        save_path += str(userId)

        if pathlib.Path(save_path).exists() == False:
            os.mkdir(save_path)

        request_time = datetime.today().strftime("%Y%m%d%H%M%S")

        save_path += "/"
        save_path += request_time

        if pathlib.Path(save_path).exists() == False:
            os.mkdir(save_path)

        save_path += "/"
        save_path += secure_filename(file.filename)

        file.save(save_path)

        # print(file.filename)
        # print(info)

        res = prediction(type, save_path)

        if res == False:
            return False
        else:
            return res

    return False


def prediction(type, path):

    eye_model_path = "../../Model/yolov5/runs/train-cls/only_eye_43/weights/best.pt"
    # eye_model_path = "../../Model/yolov5/runs/train-cls/only_eye_44/weights/best.pt"
    # eye_model_path = "../../Model/yolov5/runs/train-cls/only_eye_44_3/weights/last.pt" # 사용 x
    # eye_model_path = "../../Model/yolov5/runs/train-cls/only_eye_44_5/weights/last.pt" # 사용 x
    # eye_model_path = "../../Model/yolov5/runs/train-cls/only_eye_43_2/weights/last.pt"
    # eye_model_path = "../../Model/yolov5/runs/train-cls/only_eye_43_3/weights/last.pt"
    # eye_model_path = "../../Model/yolov5/runs/train-cls/only_eye_43_4/weights/last.pt"

    # skin_model_path = "../../Model/yolov5/runs/train-seg/only_skin_1/weights/last.pt"
    # skin_model_path = "../../Model/yolov5/runs/train-seg/only_skin_5/weights/best.pt"
    skin_model_path = "../../Model/yolov5/runs/train-seg/only_skin_7_2/weights/last.pt"


    if pathlib.Path(path).exists() == False:
        return False

    if type == "eye":

        res = flask_server_predict.main(os.path.abspath(eye_model_path), os.path.abspath(path))

        response = {
            res[0].split(' ')[0] : res[0].split(' ')[1],
            res[1].split(' ')[0] : res[1].split(' ')[1],
            res[2].split(' ')[0] : res[2].split(' ')[1],
            res[3].split(' ')[0] : res[3].split(' ')[1],
            res[4].split(' ')[0] : res[4].split(' ')[1]
        }

        print(res)

        return jsonify(response)

    elif type == "skin":

        res = flask_server_predict_seg.main(os.path.abspath(skin_model_path), os.path.abspath(path))

        response = defaultdict(float)

        if len(res) > 0:

            for data in res:

                disease = data.split(' ')[0]
                probability = data.split(' ')[1]

                if float(probability) > float(response[disease]):
                    response[disease] = probability
        # else:

        #     response['empty'] = 1

        # print(response)
        print(res)

        return jsonify(response)

    else:
        return False

    return False


if __name__ == "__main__":
    app.run(host="0.0.0.0", port=9000)