Update app.py

app.py

@@ -6,12 +6,22 @@ import uuid
 import shutil
 from pathlib import Path
 from typing import Tuple, Dict, List, Optional
+
 import gradio as gr
 import SimpleITK as sitk
 from huggingface_hub import hf_hub_download
+
 import spaces
 
 
+# Dummy function to satisfy HF Spaces GPU detection during startup
+@spaces.GPU
+def _init_gpu():
+    """Dummy function to ensure Spaces detects GPU usage at startup."""
+    import torch
+    return torch.cuda.is_available() if torch.cuda.is_available() else True
+
+
 # =========================
 # App config
 # =========================
@@ -50,6 +60,12 @@ def ensure_dirs() -> None:
     MODEL_ROOT.mkdir(parents=True, exist_ok=True)
     BIN_ROOT.mkdir(parents=True, exist_ok=True)
 
+# After ensure_dirs(), add:
+try:
+    _init_gpu()
+except Exception:
+    pass
+
 
 def is_zip(path: Path) -> bool:
     return path.suffix.lower() == ".zip"
@@ -62,7 +78,7 @@ def get_dcm2niix_bin() -> Optional[str]:
     return shutil.which("dcm2niix")
 
 
-# ---- SynthStrip (NiPreps) ----
+# ---- SynthStrip (NiPreps) without Docker ----
 def ensure_synthstrip_available() -> None:
     """
     Ensure SynthStrip from NiPreps is available, either:
@@ -284,7 +300,6 @@ def register_rigid_affine(prev_stripped: Path, new_stripped: Path, reg_dir: Path
 @spaces.GPU(duration=300)
 def run_flames_single(input_nii: Path, out_mask_path: Path, device: str = "cuda") -> Path:
     """Run FLAMeS (nnUNetv2) on a single input NIfTI and write a mask. Uses shared MODEL_ROOT."""
-    # Ensure file is accessible
     with (Path(input_nii).open("rb")):
         pass
     import tempfile
@@ -493,6 +508,7 @@ def _redact_paths(s: str) -> str:
     return s
 
 
+@spaces.GPU(duration=300)
 def run_pipeline(file1, file2, dilate_prev_radius_vox=1, min_lesion_vol_ml=0.01):
     """
     file1: previous (baseline) FLAIR (.nii/.nii.gz or DICOM .zip)
@@ -539,7 +555,7 @@ def run_pipeline(file1, file2, dilate_prev_radius_vox=1, min_lesion_vol_ml=0.01)
         registered_path, _, _ = register_rigid_affine(prev_stripped, new_stripped, reg_dir)
         registered_path = registered_path.resolve()
 
-        # FLAMeS segmentation (only this part uses GPU/zeroGPU)
+        # FLAMeS segmentation
         seg_dir = job_dir / SEG_DIR; seg_dir.mkdir(parents=True, exist_ok=True)
         prev_mask_flames = seg_dir / "prev_flames_mask.nii.gz"
         new_mask_flames  = seg_dir / "new_in_prev_space_flames_mask.nii.gz"
@@ -610,7 +626,7 @@ def run_pipeline(file1, file2, dilate_prev_radius_vox=1, min_lesion_vol_ml=0.01)
 
 
 # =========================
-# Gradio UI (consistent theme)
+# Gradio UI (refined, consistent theme)
 # =========================
 with gr.Blocks(
     title=APP_NAME,
@@ -629,6 +645,7 @@ with gr.Blocks(
         -webkit-background-clip: text;
         -webkit-text-fill-color: transparent;
     }
+
     /* ----- Run pipeline button ----- */
     #run_btn {
         display: block;
@@ -644,12 +661,14 @@ with gr.Blocks(
         transition: all 0.25s ease;
         text-transform: none !important;
     }
+
     #run_btn:hover {
         background: linear-gradient(90deg, #3da0df, #64eec8);
         transform: translateY(-1px);
         box-shadow: 0 6px 14px rgba(0, 0, 0, 0.18);
         color: #000
     }
+
     /* ----- Status box ----- */
     #status_box {
         overflow: visible !important;
@@ -663,6 +682,7 @@ with gr.Blocks(
         font-size: 16px;
         line-height: 1.45;
     }
+
     /* ----- Info & reference sections ----- */
     .info-section {
         font-size: 18px;
@@ -675,6 +695,7 @@ with gr.Blocks(
         border: 1px solid var(--border-color-primary);
         box-shadow: 0 4px 14px rgba(0,0,0,0.06);
     }
+
     .info-section h3 {
         margin-top: 0;
         margin-bottom: 12px;
@@ -683,28 +704,34 @@ with gr.Blocks(
         color: #4cafef;
         letter-spacing: -0.3px;
     }
+
     .info-section p, .info-section li {
         color: var(--body-text-color);
     }
+
     .info-section ul {
         margin-top: 6px;
         margin-bottom: 6px;
         padding-left: 24px;
         list-style-type: disc;
     }
+
     .info-section code { 
         background: var(--background-secondary);
         padding: 2px 5px;
         border-radius: 5px;
         font-size: 90%;
     }
+
     .info-section a {
         color: #4cafef;
         text-decoration: none;
     }
+
     .info-section a:hover {
         text-decoration: underline;
     }
+
     /* ----- Textual report styling ----- */
     #report {
         font-size: 20px !important;
@@ -718,6 +745,7 @@ with gr.Blocks(
         margin: 0 auto 34px auto;
         box-shadow: 0 6px 18px rgba(0,0,0,0.08);
     }
+
     #report h3 {
         margin-top: 0;
         margin-bottom: 16px;
@@ -727,21 +755,25 @@ with gr.Blocks(
         letter-spacing: -0.3px;
         text-align: left;
     }
+
     #report ul {
         margin: 10px 0 0 22px;
         padding: 0;
         list-style-type: disc;
     }
+
     #report li {
         margin-bottom: 10px;
         font-size: 20px;
         line-height: 1.8;
     }
+
     #report strong {
         color: #4cafef;
         font-weight: 600;
         font-size: 20px;
     }
+
     #report .footnote {
         font-size: 16px;
         color: #999;
@@ -758,14 +790,18 @@ with gr.Blocks(
 <div class="info-section">
   <h3>Overview</h3>
   <p>This tool detects changes in <strong>multiple sclerosis (MS) lesions</strong> between two brain MRI scans.</p>
+
   <p>Input sequence must be <strong>isotropic 3D FLAIR</strong> in 
   <code>.nii/.nii.gz</code> (NIfTI) or DICOM (<code>.zip</code>) format. <br>
   If DICOM is provided, images are automatically converted to NIfTI using 
   <em>dcm2niix</em>.</p>
+
   <p>Processing includes skull stripping with <em>NiPreps SynthStrip</em> package, 
   rigid/affine co-registration of the two scans with SimpleITK, 
   and lesion segmentation using <em>FLAMeS</em> deep learning model.</p>
+
   <p>Lesion difference masks between the two scans are then calculated and made available for download.</p>
+
   <p><strong>Note: This application is a <em>research preview</em>. 
   For clinical reporting, all results should be reviewed and validated by a qualified radiologist.</strong></p>
 </div>
@@ -784,6 +820,7 @@ with gr.Blocks(
     <li>After processing, download the ZIP file and open the NIfTI outputs in your preferred neuroimaging viewer
         (e.g. ITK-SNAP, FSLeyes, 3D Slicer) to inspect the lesions and overlays.</li>
   </ul>
+
   <p style="margin-top:16px;"><strong>Advanced options:</strong></p>
   <ul>
     <li><em>Dilate previous mask (voxels):</em> Expands the baseline lesion mask slightly 
@@ -829,12 +866,14 @@ Li X, Morgan PS, Ashburner J, Smith J, Rorden C (2016).
 <strong>J Neurosci Methods</strong> 264:47–56.  
 <a href="https://doi.org/10.1016/j.jneumeth.2016.03.001" target="_blank">📄 DOI: 10.1016/j.jneumeth.2016.03.001</a>
 </li>
+
 <li>
 Hoopes A, Mora JS, Dalca AV, Fischl B*, Hoffmann M* (2022). 
 <em>SynthStrip: Skull-Stripping for Any Brain Image.</em> 
 <strong>NeuroImage</strong> 260:119474.  
 <a href="https://doi.org/10.1016/j.neuroimage.2022.119474" target="_blank">📄 DOI: 10.1016/j.neuroimage.2022.119474</a>
 </li>
+
 <li>
 Dereskewicz E, La Rosa F, Dos Santos Silva J, et al. (2025). 
 <em>FLAMeS: A Robust Deep Learning Model for Automated Multiple Sclerosis Lesion Segmentation.</em>