The current registered: [<monai.data.image_reader.NumpyReader object at 0x7fc8b1892980>, <monai.data.image_reader.PILReader object at 0x7fc8b1892920>]. #6798
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by
KumoLiu
SawinKumar
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preproc_transforms = Compose(
[
LoadImaged(keys=["image"]),
EnsureChannelFirstd(keys="image"),
Orientationd(keys=["image"], axcodes="RAS"),
NormalizeIntensityd(keys="image", nonzero=True, channel_wise=True),
]
)
model.load_state_dict(torch.load("models/best_metric_model_epoch_40.pth"))
processed_data = preproc_transforms({'image': [tumor_file_path]})The above code giving the error only on cpu machines. When I try to change the map_location to cpu This is the error |
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Answered by
KumoLiu
Jul 31, 2023
Replies: 1 comment 8 replies
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Hi @SawinKumar, did you put your model on the CPU? Thanks! |
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8 replies
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This is the exact error bro File "/workspaces/Brain-tumor-ui/venv/lib/python3.10/site-packages/monai/transforms/compose.py", line 111, in execute_compose
data = apply_transform(
File "/workspaces/Brain-tumor-ui/venv/lib/python3.10/site-packages/monai/transforms/transform.py", line 171, in apply_transform
raise RuntimeError(f"applying transform {transform}") from e
RuntimeError: applying transform <monai.transforms.io.dictionary.LoadImaged object at 0x7f022a2bba90> |
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Could you please paste the whole error message? |
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whole code import gradio as gr
import numpy as np
import time
import matplotlib.pyplot as plt
from PIL import Image
import torch
import os
from monai.networks.nets import SegResNet
from monai.inferers import sliding_window_inference
from monai.transforms import (
Activations,
AsDiscrete,
Compose,
LoadImaged,
NormalizeIntensityd,
Orientationd,
EnsureChannelFirstd,
)
preproc_transforms = Compose(
[
LoadImaged(keys=["image"]),
EnsureChannelFirstd(keys="image"),
Orientationd(keys=["image"], axcodes="RAS"),
NormalizeIntensityd(keys="image", nonzero=True, channel_wise=True),
]
)
post_trans = Compose([Activations(sigmoid=True), AsDiscrete(threshold=0.5)])
model = SegResNet(
blocks_down=[1, 2, 2, 4],
blocks_up=[1, 1, 1],
init_filters=16,
in_channels=4,
out_channels=3,
dropout_prob=0.2,
).to('cpu')
model.load_state_dict(torch.load("models/best_metric_model_epoch_40.pth",map_location='cpu'))
def inference(input):
def _compute(input):
return sliding_window_inference(
inputs=input,
roi_size=(240, 240, 160),
sw_batch_size=1,
predictor=model,
overlap=0.5,
)
return _compute(input)
title = 'Detect and Segment Brain Tumors 🧠'
description = '''
'''
def detector(tumor_file, slice_number, channel=0):
print(tumor_file)
tumor_file_path = tumor_file.name
print(tumor_file_path)
processed_data = preproc_transforms({'image': [tumor_file_path]})
# tensor_3d_input = processed_data['image'].unsqueeze(0).to('cpu')
# with torch.no_grad():
# output = inference(tensor_3d_input)
# print(output.shape)
# img_slice = tensor_3d_input[0][0, :, :, slice_number]
# plt.imshow(img_slice, cmap='gray')
# input_image_path = f"input_img_channel{channel}.png"
# plt.axis('off')
# plt.savefig(input_image_path, bbox_inches='tight', pad_inches=0)
# channel_image = np.asarray(Image.open(input_image_path))
# os.remove(input_image_path)
# output_image_path = f"ouput_img_channel{channel}.png"
# plt.imshow(post_trans(output[0][1, :, :, 110]))
# plt.axis('off')
# plt.savefig(output_image_path, bbox_inches='tight', pad_inches=0)
# segment_image = np.asarray(Image.open(output_image_path))
# os.remove(output_image_path)
return (np.array([[1]]), np.array([[1]]), "You will live for a few more days")
interface = gr.Interface(fn=detector, inputs=[gr.File(label="Tumor File"),
gr.Slider(0, 200, 50, label="Slice Number"),
gr.Slider(0, 4, 0, label="Slice Number")],
outputs=[gr.Image(),
gr.Image(label='label'),
gr.Textbox(label="Medical Summary")], title=title,
description=description)
interface.launch(debug=True)Whole error Once you upload the file to gradio you will get this error |
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Hi @SawinKumar, could you please try to install Nibabel? Seems you didn't have a suitable reader. Thanks! |
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Answer selected by
SawinKumar
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Thanks a lot I'm breaking down into tears 😂 , I'm also grateful to you bro |
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Hi @SawinKumar, could you please try to install Nibabel? Seems you didn't have a suitable reader.
Thanks!