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| import gradio as gr | |
| import subprocess | |
| import os | |
| import shutil | |
| import uuid | |
| import zipfile | |
| import nibabel as nib | |
| import matplotlib.pyplot as plt | |
| def run_segmentation(uploaded_file, modality): | |
| job_id = str(uuid.uuid4()) | |
| input_filename = f"input_{job_id}.nii.gz" | |
| output_folder = f"segmentations_{job_id}" | |
| if isinstance(uploaded_file, str): | |
| shutil.copy(uploaded_file, input_filename) | |
| elif hasattr(uploaded_file, "read"): | |
| with open(input_filename, "wb") as f: | |
| f.write(uploaded_file.read()) | |
| else: | |
| return None, None, "Invalid file input." | |
| command = ["TotalSegmentator", "-i", input_filename, "-o", output_folder] | |
| if modality == "MR": | |
| command.extend(["--task", "total_mr"]) | |
| try: | |
| subprocess.run(command, check=True) | |
| except subprocess.CalledProcessError as e: | |
| error_message = f"Error during segmentation: {e}" | |
| if os.path.exists(input_filename): os.remove(input_filename) | |
| if os.path.exists(output_folder): shutil.rmtree(output_folder) | |
| return None, None, error_message | |
| zip_filename = f"segmentations_{job_id}.zip" | |
| with zipfile.ZipFile(zip_filename, "w", zipfile.ZIP_DEFLATED) as zipf: | |
| for root, dirs, files in os.walk(output_folder): | |
| for file in files: | |
| file_path = os.path.join(root, file) | |
| arcname = os.path.relpath(file_path, output_folder) | |
| zipf.write(file_path, arcname) | |
| seg_files = [os.path.join(output_folder, f) for f in os.listdir(output_folder) if f.endswith('.nii.gz')] | |
| image_filename = None | |
| if seg_files: | |
| seg_file = seg_files[0] | |
| try: | |
| seg_img = nib.load(seg_file) | |
| seg_data = seg_img.get_fdata() | |
| slice_idx = seg_data.shape[2] // 2 | |
| seg_slice = seg_data[:, :, slice_idx] | |
| plt.figure(figsize=(6, 6)) | |
| plt.imshow(seg_slice.T, cmap="gray", origin="lower") | |
| plt.axis('off') | |
| image_filename = f"segmentation_preview_{job_id}.png" | |
| plt.savefig(image_filename, bbox_inches='tight') | |
| plt.close() | |
| except Exception as e: | |
| print(f"Error creating preview: {e}") | |
| image_filename = None | |
| os.remove(input_filename) | |
| shutil.rmtree(output_folder) | |
| return zip_filename, image_filename, "Segmentation completed successfully." | |
| with gr.Blocks() as demo: | |
| gr.Markdown("# TotalSegmentator Gradio App") | |
| gr.Markdown( | |
| "Upload a CT or MR image (in NIfTI format) and run segmentation using TotalSegmentator. " | |
| "For MR images, the task flag is set accordingly. A preview of one segmentation slice will be displayed." | |
| ) | |
| with gr.Row(): | |
| uploaded_file = gr.File(label="Upload NIfTI Image (.nii.gz)") | |
| modality = gr.Radio(choices=["CT", "MR"], label="Select Image Modality", value="CT") | |
| with gr.Row(): | |
| zip_output = gr.File(label="Download Segmentation Output (zip)") | |
| preview_output = gr.Image(label="Segmentation Preview") | |
| status_output = gr.Textbox(label="Status", interactive=False) | |
| run_btn = gr.Button("Run Segmentation") | |
| run_btn.click(fn=run_segmentation, inputs=[uploaded_file, modality], outputs=[zip_output, preview_output, status_output]) | |
| demo.launch() | |