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尝试使用 yolov4 创建 webapp，已将 yolov4 权重转换为 tensorflow 权重，当我运行app.py文件时，它显示错误AttributeError: 'InteractiveSession' object has no attribute 'tiny'。

使用 2 个文件app.py和app_helper.py。

app_helper.py


import tensorflow as tf
import cv2
from PIL import Image
import numpy as np
from core.yolov4 import YOLOv4,YOLOv4_tiny,decode,decode_tf,filter_boxes
from core.utils import load_weights,read_class_names,image_preprocess,draw_bbox,load_config
from tensorflow.compat.v1 import ConfigProto
from tensorflow.compat.v1 import InteractiveSession

def get_images(image_path,image_name):
    class_path='./data/classes/coco.names'
    weights_path='./checkpoints/yolov4-416'
    NUM_CLASS=80
    tiny=False
    size=416
    output='/data/detections'
    framework='tf'
    image='./data/images/kite.jpg'
    model='yolov4'
    iou=0.45
    score=0.25

    config = ConfigProto()
    config.gpu_options.allow_growth = True
    session = InteractiveSession(config=config)
    STRIDES, ANCHORS, NUM_CLASS, XYSCALE = load_config(session)   #utils.
    input_size = size
    image_path = image

    original_image = cv2.imread(image_path)
    original_image = cv2.cvtColor(original_image, cv2.COLOR_BGR2RGB)

    # image_data = utils.image_preprocess(np.copy(original_image), [input_size, input_size])
    image_data = cv2.resize(original_image, (input_size, input_size))
    image_data = image_data / 255.
    # image_data = image_data[np.newaxis, ...].astype(np.float32)

    images_data = []
    for i in range(1):
        images_data.append(image_data)
    images_data = np.asarray(images_data).astype(np.float32)

    if framework == 'tflite':
        interpreter = tf.lite.Interpreter(model_path=weights_path)  #replaced FLAGS.weights
        interpreter.allocate_tensors()
        input_details = interpreter.get_input_details()
        output_details = interpreter.get_output_details()
        print(input_details)
        print(output_details)
        interpreter.set_tensor(input_details[0]['index'], images_data)
        interpreter.invoke()
        pred = [interpreter.get_tensor(output_details[i]['index']) for i in range(len(output_details))]
        if model == 'yolov3' and tiny == True:
            boxes, pred_conf = filter_boxes(pred[1], pred[0], score_threshold=0.25,
                                            input_shape=tf.constant([input_size, input_size]))
        else:
            boxes, pred_conf = filter_boxes(pred[0], pred[1], score_threshold=0.25,
                                            input_shape=tf.constant([input_size, input_size]))
    else:
        saved_model_loaded = tf.saved_model.load(weights_path, tags=[tag_constants.SERVING])  #weights  #
        infer = saved_model_loaded.signatures['serving_default']
        batch_data = tf.constant(images_data)
        pred_bbox = infer(batch_data)
        for key, value in pred_bbox.items():
            boxes = value[:, :, 0:4]
            pred_conf = value[:, :, 4:]

    boxes, scores, classes, valid_detections = tf.image.combined_non_max_suppression(
        boxes=tf.reshape(boxes, (tf.shape(boxes)[0], -1, 1, 4)),
        scores=tf.reshape(
            pred_conf, (tf.shape(pred_conf)[0], -1, tf.shape(pred_conf)[-1])),
        max_output_size_per_class=50,
        max_total_size=50,
        iou_threshold=iou,
        score_threshold=score
    )
    pred_bbox = [boxes.numpy(), scores.numpy(), classes.numpy(), valid_detections.numpy()]
    image = draw_bbox(original_image, pred_bbox)   #utils.
    # image = utils.draw_bbox(image_data*255, pred_bbox)
    image = Image.fromarray(image.astype(np.uint8))
    image.show()
    image = cv2.cvtColor(np.array(image), cv2.COLOR_BGR2RGB)
    cv2.imwrite(output, image)

和app.py

from flask import Flask, render_template, Response,  request, session, redirect, url_for, send_from_directory,flash,jsonify
from werkzeug.utils import secure_filename

from PIL import Image
import os
import sys
import cv2
from app_helper import *
from flask_cors import CORS,cross_origin

app=Flask(__name__)

upload_folder='./data/images'

app.config['upload_folder'] = upload_folder


@app.route("/")
def index():
    return render_template("index.html")


@app.route("/about")
def about():
    return render_template("about.html")


@app.route('/uploader', methods=['GET', 'POST'])
def upload_file():
    if request.method == 'POST':
        f = request.files['file']
        # create a secure filename
        filename = secure_filename(f.filename)
        print(filename)
        # save file to data/images    #/static/uploads
        filepath = os.path.join(app.config['upload_folder'], filename)
        print(filepath)
        f.save(filepath)
        get_images(filepath,filename)

        return render_template("uploaded.html", display_detection=filepath, fname=filepath)


if __name__ == '__main__':
    app.run(port=7000, debug=True)

请帮助我了解如何克服此错误

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