从 streamlit file_uploader 获取错误

Posted 2023-03-29

【中文标题】从 streamlit file_uploader 获取错误

【英文标题】：getting an error from streamlit file_uploader

【发布时间】：2021-08-22 06:39:10

【问题描述】：

我在尝试从 streamlit file_uploader 加载图像来预测图像时收到此错误。当我尝试直接在 ide 中加载图像时，该过程工作正常。但问题出在 streamlit file_uploader。我无法确定streamlit 以哪种文件类型上传文件。请帮助我了解如何上传自定义图像并使用 Keras 模型进行预测。

它显示了这个错误。

ValueError: Attempt to convert a value (<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=474x266 at 0x1C7B84190A0>) with an unsupported type (<class 'PIL.JpegImagePlugin.JpegImageFile'>) to a Tensor.

我的代码是

import tensorflow as tf
import streamlit as st
from PIL import  Image

class_names = ['apple_pie',....'] # total 101 food name.

# loading the model
model = tf.keras.models.load_model('effi_080_second.h5') 

file = st.file_uploader('Upload a file', type='jpg') # asking for file

image = Image.open(file)
st.image(image) # showing the image.


img = tf.io.read_file(file)
img = tf.image.decode_image(img)
# rsize the image
img = tf.image.resize(image, size=(224,224))
img = tf.expand_dims(img, axis=0)
pred = model.predict(img)

pred_cls = class_names[pred.argmax()] # gettting the class name index
st.write(pred_cls) # writting the class name```



The full error is
   `ValueError: Attempt to convert a value (<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=474x266 at 0x1C7B84190A0>) with an unsupported type (<class 'PIL.JpegImagePlugin.JpegImageFile'>) to a Tensor.
Traceback:
File "e:\anaconda3\envs\webapp_streamlit\lib\site-packages\streamlit\script_runner.py", line 338, in _run_script
    exec(code, module.__dict__)
File "E:\WebApp_streamlit\image_process.py", line 120, in <module>
    img = tf.image.resize(image, size=(224,224))
File "e:\anaconda3\envs\webapp_streamlit\lib\site-packages\tensorflow\python\util\dispatch.py", line 201, in wrapper
    return target(*args, **kwargs)
File "e:\anaconda3\envs\webapp_streamlit\lib\site-packages\tensorflow\python\ops\image_ops_impl.py", line 1540, in resize_images_v2
    return _resize_images_common(
File "e:\anaconda3\envs\webapp_streamlit\lib\site-packages\tensorflow\python\ops\image_ops_impl.py", line 1210, in _resize_images_common
    images = ops.convert_to_tensor(images, name='images')
File "e:\anaconda3\envs\webapp_streamlit\lib\site-packages\tensorflow\python\framework\ops.py", line 1499, in convert_to_tensor
    ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
File "e:\anaconda3\envs\webapp_streamlit\lib\site-packages\tensorflow\python\framework\constant_op.py", line 338, in _constant_tensor_conversion_function
    return constant(v, dtype=dtype, name=name)
File "e:\anaconda3\envs\webapp_streamlit\lib\site-packages\tensorflow\python\framework\constant_op.py", line 263, in constant
    return _constant_impl(value, dtype, shape, name, verify_shape=False,
File "e:\anaconda3\envs\webapp_streamlit\lib\site-packages\tensorflow\python\framework\constant_op.py", line 275, in _constant_impl
    return _constant_eager_impl(ctx, value, dtype, shape, verify_shape)
File "e:\anaconda3\envs\webapp_streamlit\lib\site-packages\tensorflow\python\framework\constant_op.py", line 300, in _constant_eager_impl
    t = convert_to_eager_tensor(value, ctx, dtype)
File "e:\anaconda3\envs\webapp_streamlit\lib\site-packages\tensorflow\python\framework\constant_op.py", line 98, in convert_to_eager_tensor
    return ops.EagerTensor(value, ctx.device_name, dtype)`


Please help me with this, I want to know how to predict an image from streamlit file uploader and then predict it from the keras model.

【参考方案1】：

由于您已经在缓冲区中有图像，您可以试试这个。

import streamlit as st
from PIL import Image
import numpy as np
import tensorflow as tf

file = st.file_uploader("Upload an image", type=["png", "jpg", "jpeg"])

if file is not None:
    image = Image.open(file)

    st.image(
        image,
        caption=f"You amazing image has shape",
        use_column_width=True,
    )

    img_array = np.array(image)
    img = tf.image.resize(img_array, size=(224,224))
    img = tf.expand_dims(img, axis=0)