Add All Folders

2026-02-08 04:38:10 +03:30
commit 9bb57e4799
191 changed files with 8469 additions and 0 deletions
@@ -0,0 +1,89 @@
+import os
+import time
+import json
+import luigi
+from pathlib import Path
+import pysera
+from engine.utils import json_safe
+
+class FeatureExtraction(luigi.Task):
+    artifacts_dir = luigi.Parameter(default="artifacts")
+    temp_dir = luigi.Parameter(default=r"C:\Users\Omen16\AppData\Local\ViSERA\res\memory\memmap\pysera_temp")
+
+    def requires(self):
+        from engine.tasks_filter import ImageFilter
+        from engine.tasks_maskreg import MaskRegistration
+        return {
+            "filter": ImageFilter(artifacts_dir=self.artifacts_dir),
+            "maskreg": MaskRegistration(artifacts_dir=self.artifacts_dir)
+        }
+
+    def output(self):
+        return luigi.LocalTarget(os.path.join(self.artifacts_dir, "radiomics_index.json"))
+
+    def run(self):
+        # 
+        filt_index = os.path.join(self.artifacts_dir, "filtered_index.txt")
+        mask_index = os.path.join(self.artifacts_dir, "mask_registered_index.txt")
+        with open(filt_index, "r") as f:
+            filtered_paths = [line.strip() for line in f if line.strip()]
+        with open(mask_index, "r") as f:
+            mask_paths = [line.strip() for line in f if line.strip()]
+
+        results = []
+        for img, mask in zip(filtered_paths, mask_paths):
+            start = time.time()
+            result = pysera.process_batch(
+                image_input=img,
+                mask_input=mask,
+                output_path=self.artifacts_dir,
+                categories="diag,morph,glcm,glrlm,glszm,ngtdm,ngldm",
+                dimensions="1st,3D",
+                bin_size=25,
+                roi_num=2,
+                roi_selection_mode="per_region",
+                apply_preprocessing=True,
+                feature_value_mode="REAL_VALUE",
+                min_roi_volume=50,
+                enable_parallelism=True,
+                num_workers="4",
+                report="info",
+                temporary_files_path=str(self.temp_dir),
+                IBSI_based_parameters={
+                    "radiomics_DataType": "CT",
+                    "radiomics_DiscType": "FBS",
+                    "radiomics_isScale": 0,
+                    "radiomics_VoxInterp": "Nearest",
+                    "radiomics_ROIInterp": "Nearest",
+                    "radiomics_isotVoxSize": 2.0,
+                    "radiomics_isotVoxSize2D": 2.0,
+                    "radiomics_isIsot2D": 0,
+                    "radiomics_isGLround": 0,
+                    "radiomics_isReSegRng": 0,
+                    "radiomics_isOutliers": 0,
+                    "radiomics_isQuntzStat": 1,
+                    "radiomics_ReSegIntrvl01": -1000,
+                    "radiomics_ReSegIntrvl02": 400,
+                    "radiomics_ROI_PV": 0.5,
+                    "radiomics_qntz": "Uniform",
+                    "radiomics_IVH_Type": 3,
+                    "radiomics_IVH_DiscCont": 1,
+                    "radiomics_IVH_binSize": 2.0,
+                },
+            )
+            elapsed = round(time.time() - start, 2)
+
+            safe_result = json_safe(result)
+            case_json = os.path.join(self.artifacts_dir, f"{Path(img).name}_radiomics.json")
+            with open(case_json, "w", encoding="utf-8") as f:
+                json.dump(safe_result, f, indent=2, ensure_ascii=False)
+
+            results.append({
+                "image": img,
+                "mask": mask,
+                "elapsed_seconds": elapsed,
+                "result_file": case_json,
+            })
+
+        with self.output().open("w") as f:
+            json.dump({"radiomics_results": results}, f, indent=2, ensure_ascii=False)