ValueError：层顺序从未被调用，因此没有定义的输入

Question

我编写了这个精简代码来检测一个人是否戴着口罩，如果没有，则使用 DeepFace 库显示他们的估计年龄和性别。我使用张量流来使用预训练模型 MobileNet v2 并使用 ImageNet 数据集的权重。我正在使用 OpenCV 从网络摄像头捕获实时视频源，并使用 DeepFace 对它返回的帧进行分析。但我在 DeepFace.analyze() 函数中遇到 ValueError 这是代码：

import streamlit as st
import cv2
import numpy as np
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.image import img_to_array
from tensorflow.keras.applications.mobilenet_v2 import preprocess_input
from deepface import DeepFace

# Load the trained mask detection model
model = load_model("mask_detection_model.h5")

# Load the pre-trained face detection model
face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')

# Create a function for real-time mask detection
def detect_mask(frame):
    # Preprocess the frame
    resized_frame = cv2.resize(frame, (128, 128))
    resized_frame = img_to_array(resized_frame)
    resized_frame = preprocess_input(resized_frame)
    resized_frame = np.expand_dims(resized_frame, axis=0)

    # Perform prediction
    predictions = model.predict(resized_frame)
    return predictions

# Streamlit web app
st.title("Real-time Face Mask Detection")

# Open the webcam
cap = cv2.VideoCapture(0)

if not cap.isOpened():
    st.error("Error: Could not open webcam.")

else:
    stframe = st.empty()
    while True:
        ret, frame = cap.read()
        if not ret:
            st.error("Error: Unable to capture frame.")
            break
        
        # Perform mask detection
        predictions = detect_mask(frame)
        label = "Mask" if np.argmax(predictions) == 1 else "No Mask"
        color = (0, 255, 0) if label == "Mask" else (0, 0, 255)

        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5, minSize=(100, 100))
        
        # Display the frame with the label
        for (x, y, w, h) in faces:
            face = frame[y:y + h, x:x + w]

            # Perform mask detection
            predictions = detect_mask(frame)
            label = "Mask" if np.argmax(predictions) == 1 else "No Mask"
            color = (0, 255, 0) if label == "Mask" else (0, 0, 255)

            # If no mask is detected, estimate age and gender
            if label == "No Mask":
                results = DeepFace.analyze(img_path = frame[y:y+h, x:x+w], actions=['age', 'gender'], enforce_detection=False)  #<-- Getting error at this line
                results = results[0]
                age = results['age']
                gender = results['dominant_gender']
                # print(results)
                # print(type(results[0]))

                # Display age and gender estimation
                cv2.putText(frame, f'Age: {age:.1f} years', (x, y - 60), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 0, 255), 2)
                cv2.putText(frame, f'Gender: {gender}', (x, y - 40), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0, 0, 255), 2)

            # Display mask detection result
            cv2.rectangle(frame, (x, y), (x + w, y + h), color, 2)
            cv2.putText(frame, label, (x,y-10), cv2.FONT_HERSHEY_SIMPLEX, 1, color, 2)
        
        # Convert the frame to RGB for Streamlit
        frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
        
        # Display the frame using Streamlit
        stframe.image(frame_rgb, channels="RGB", use_column_width=True)
        
        cv2.waitKey(1)

    cap.release()
    cv2.destroyAllWindows()

这是我运行时的错误

streamlit run app.py

：

File "D:\Machine Learning Projects\Face Mask Detection\.venv\Lib\site-packages\streamlit\runtime\scriptrunner\script_runner.py", line 542, in _run_script
    exec(code, module.__dict__)
File "D:\Machine Learning Projects\Face Mask Detection\app.py", line 63, in <module>
    results = DeepFace.analyze(img_path = frame[y:y+h, x:x+w], actions=['age', 'gender'], enforce_detection=False)
              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\Machine Learning Projects\Face Mask Detection\.venv\Lib\site-packages\deepface\DeepFace.py", line 222, in analyze
    return demography.analyze(
           ^^^^^^^^^^^^^^^^^^^
File "D:\Machine Learning Projects\Face Mask Detection\.venv\Lib\site-packages\deepface\modules\demography.py", line 157, in analyze
    apparent_age = modeling.build_model("Age").predict(img_content)
                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\Machine Learning Projects\Face Mask Detection\.venv\Lib\site-packages\deepface\modules\modeling.py", line 46, in build_model
    model_obj[model_name] = model()
                            ^^^^^^^
File "D:\Machine Learning Projects\Face Mask Detection\.venv\Lib\site-packages\deepface\extendedmodels\Age.py", line 32, in __init__
    self.model = load_model()
                 ^^^^^^^^^^^^
File "D:\Machine Learning Projects\Face Mask Detection\.venv\Lib\site-packages\deepface\extendedmodels\Age.py", line 61, in load_model
    age_model = Model(inputs=model.input, outputs=base_model_output)
                             ^^^^^^^^^^^
File "D:\Machine Learning Projects\Face Mask Detection\.venv\Lib\site-packages\keras\src\ops\operation.py", line 216, in input
    return self._get_node_attribute_at_index(0, "input_tensors", "input")
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\Machine Learning Projects\Face Mask Detection\.venv\Lib\site-packages\keras\src\ops\operation.py", line 247, in _get_node_attribute_at_index
    raise ValueError(
ValueError: The layer sequential has never been called and thus has no defined input.

我已经阅读了 DeepFace 的文档，但无法找出导致此错误的可能原因。

请尽快帮忙，我将不胜感激。

Answer 1

尝试更改您使用的模型，我也遇到了这个错误，但通过使用除默认模型之外的其他脸部模型来缓解它，尽管在我的情况下我正在验证脸部，目前可用的模型是：

models = [
    "VGG-Face", 
    "Facenet", 
    "Facenet512", 
    "OpenFace", 
    "DeepFace", 
    "DeepID", 
    "ArcFace", 
    "Dlib", 
    "SFace",
    "GhostFaceNet",
    ]

如果模型选项在分析时不可用，您可以通过首先删除已下载的权重来重新加载权重，或者您可以使用 deepface 中的分析功能来使用您想要的自定义模型