.sh files added to run export and inference with bash

scripts/coyote_protector_xtc_gui_ready_test/bash_launcher.py

@@ -0,0 +1,134 @@
+#!/usr/bin/env python3
+"""
+bash_launcher.py
+Launches routine_detection_v3.sh with specified arguments.
+Can be run from CDS to orchestrate the complete XTC workflow.
+
+USAGE:
+    python bash_launcher.py [OPTIONS]
+    python bash_launcher.py --help
+
+EXAMPLES:
+    # Run with defaults
+    python bash_launcher.py
+
+    # Run with custom parameters
+    python bash_launcher.py --run_number=61 --exp_number=mfx101346325 --max_events=80000
+
+    # Run with specific user
+    python bash_launcher.py --user=pmonteil --run_number=100
+"""
+
+import argparse
+import subprocess
+import sys
+from pathlib import Path
+
+
+def eprint(msg):
+    """Write message to stderr (compatible with older Python)."""
+    sys.stderr.write(str(msg) + "\n")
+
+
+def main():
+    parser = argparse.ArgumentParser(
+        description="Launch coyote XTC detection routine via bash",
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+        epilog=__doc__
+    )
+
+    parser.add_argument(
+        "--user",
+        default="pmonteil",
+        help="Username for SSH to SDF (default: pmonteil)"
+    )
+    parser.add_argument(
+        "--run_number",
+        type=int,
+        default=61,
+        help="LCLS run number to process (default: 61)"
+    )
+    parser.add_argument(
+        "--exp_number",
+        default="mfx101346325",
+        help="Experiment identifier (default: mfx101346325)"
+    )
+    parser.add_argument(
+        "--save_normalized",
+        type=int,
+        choices=[0, 1],
+        default=1,
+        help="Save normalized images (1=yes, 0=no, default: 1)"
+    )
+    parser.add_argument(
+        "--max_events",
+        type=int,
+        default=10000,
+        help="Maximum events to process (default: 10000)"
+    )
+    parser.add_argument(
+        "--use_normalized",
+        type=int,
+        choices=[0, 1],
+        default=1,
+        help="Use normalized images for inference (1=yes, 0=no, default: 1)"
+    )
+    parser.add_argument(
+        "--dry_run",
+        action="store_true",
+        help="Print command without executing"
+    )
+
+    args = parser.parse_args()
+
+    # Get the script path (should be in same directory)
+    script_path = Path(__file__).parent / "routine_detection_v3.sh"
+
+    if not script_path.exists():
+        eprint("[ERROR] Script not found: {}".format(script_path))
+        sys.exit(1)
+
+    # Build command
+    cmd = [
+        "bash",
+        str(script_path),
+        "--user={}".format(args.user),
+        "RUN_NUMBER={}".format(args.run_number),
+        "EXP_NUMBER={}".format(args.exp_number),
+        "SAVE_NORMALIZED={}".format(args.save_normalized),
+        "MAX_EVENTS={}".format(args.max_events),
+        "USE_NORMALIZED={}".format(args.use_normalized),
+    ]
+
+    print("[INFO] ============================================")
+    print("[INFO] COYOTE XTC DETECTION LAUNCHER")
+    print("[INFO] ============================================")
+    print("[INFO] User: {}".format(args.user))
+    print("[INFO] Run Number: {}".format(args.run_number))
+    print("[INFO] Experiment: {}".format(args.exp_number))
+    print("[INFO] Save Normalized: {}".format(args.save_normalized))
+    print("[INFO] Max Events: {}".format(args.max_events))
+    print("[INFO] Use Normalized: {}".format(args.use_normalized))
+    print("[INFO] ============================================")
+    print()
+
+    print("[INFO] Command: {}".format(" ".join(cmd)))
+    print()
+
+    if args.dry_run:
+        print("[INFO] DRY RUN MODE - Command not executed")
+        return 0
+
+    try:
+        result = subprocess.run(cmd, check=False)
+        return result.returncode
+    except KeyboardInterrupt:
+        eprint("\n[INFO] Interrupted by user")
+        return 130
+    except Exception as e:
+        eprint("[ERROR] Failed to execute command: {}".format(e))
+        return 1
+
+
+if __name__ == "__main__":
+    sys.exit(main())

scripts/coyote_protector_xtc_gui_ready_test/inference_coyote_xtc.py

@@ -1,18 +1,16 @@
-
-## same as test_xtc/inference_coyote.py but with argument parsing
+#!/usr/bin/env python3
 """
-YOLOv8 Inference Script → CSV (sizes)
+YOLOv8 Inference Script → CSV (sizes) + above-threshold CSV
 ------------------------------------------------------------
 - Runs YOLO inference on a folder of images
 - Computes longest side per detection in px and μm
 - Flags detections larger than a given μm threshold
+- Writes:
+    1) results_csv/measurements_complete.csv  (ALL detections)
+    2) results_csv/measurements_above_threshold.csv (ONLY detections above threshold)
 
 USAGE:
     python inference_coyote_xtc.py <chip_pic_dir>
-
-EDIT THESE BEFORE RUNNING:
- - weights_path: Path to your trained YOLO weights (.pt)
- - px_to_um:     Pixel-to-micron conversion factor for your setup
 """
 
 import os
@@ -37,27 +35,23 @@
 # Paths / parameters
 # -------------------------
 weights_path = (
-    "/sdf/home/p/pmonteil/coyote_protector_test_PL_labeling_tries_v3_run61_mfx101346325_200_random/scripts/runs/detect/train_150epochs_v11_merged/weights/best.pt"
+    "/sdf/home/p/pmonteil/coyote_protector_test_PL_labeling_tries_v3_run61_mfx101346325_200_random/scripts/"
+    "runs/detect/train_150epochs_v11_merged/weights/best.pt"
 )
 
-'''
-weights_path = (
-    "/sdf/home/p/pmonteil/prjlumine22/results/pmonteil/"
-    "coyote_beamtime_19jan/weight_yolov11n_150epochs.pt"
-)
-'''
-
 mag_factor = 5.56     # optical magnification
 px_size = 3.45        # pixel size (μm)
-dowsamp_factor = 2  # if images were downsampled before inference
-px_to_um = px_size*dowsamp_factor / mag_factor
-alert_um = 50.0 #threshold, in μm, above which to flag detections
+dowsamp_factor = 2    # if images were downsampled before inference
+px_to_um = px_size * dowsamp_factor / mag_factor
+alert_um = 50.0       # threshold, in μm, above which to flag detections
 
 # Output CSV directory
-#out_dir = Path("runs/size_measurements")
 out_dir = Path("results_csv")
 out_dir.mkdir(parents=True, exist_ok=True)
-csv_path = out_dir / "measurements.csv"
+
+csv_all_tmp = out_dir / "measurements.csv"
+csv_all_final = out_dir / "measurements_complete.csv"
+csv_above = out_dir / "measurements_above_threshold.csv"
 
 # -------------------------
 # Load model
@@ -74,24 +68,32 @@
 )
 
 # -------------------------
-# Write CSV
+# CSV header
 # -------------------------
-with open(csv_path, "w", newline="") as f:
-    writer = csv.writer(f)
-    writer.writerow([
-        "image",
-        "det_idx",
-        "class_id",
-        "class_name",
-        "confidence",
-        "x_center_px",
-        "y_center_px",
-        "width_px",
-        "height_px",
-        "longest_px",
-        "longest_um",
-        "alert"
-    ])
+header = [
+    "image",
+    "det_idx",
+    "class_id",
+    "class_name",
+    "confidence",
+    "x_center_px",
+    "y_center_px",
+    "width_px",
+    "height_px",
+    "longest_px",
+    "longest_um",
+    "alert"
+]
+
+# -------------------------
+# Write BOTH CSVs
+# -------------------------
+with open(csv_all_tmp, "w", newline="") as f_all, open(csv_above, "w", newline="") as f_above:
+    w_all = csv.writer(f_all)
+    w_above = csv.writer(f_above)
+
+    w_all.writerow(header)
+    w_above.writerow(header)
 
     for r in results:
         img_name = os.path.basename(r.path)
@@ -111,14 +113,16 @@
             cls_name = model.names.get(cls_id, str(cls_id))
             conf = float(confs[i]) if confs.size > i else float("nan")
 
-            alert_flag = "STOP" if longest_um > alert_um else ""
-            if alert_flag:
+            is_above = longest_um > alert_um
+            alert_flag = "STOP" if is_above else ""
+
+            if is_above:
                 print(
                     f"[STOP] {img_name} — det {i+1}: "
                     f"{longest_um:.2f} μm > {alert_um} μm → Stop the beam"
                 )
 
-            writer.writerow([
+            row = [
                 img_name,
                 i + 1,
                 cls_id,
@@ -131,12 +135,21 @@
                 f"{longest_px:.2f}",
                 f"{longest_um:.2f}",
                 alert_flag
-            ])
+            ]
+
+            # Write to "all detections"
+            w_all.writerow(row)
+
+            # Write to "above threshold only"
+            if is_above:
+                w_above.writerow(row)
 
-print(f"\nCSV saved to: {csv_path}")
+print(f"\nCSV (all) saved to: {csv_all_tmp}")
+print(f"CSV (above threshold only) saved to: {csv_above}")
 
-# Rename CSV after completion
-final_csv_path = out_dir / "measurements_complete.csv"
-csv_path.rename(final_csv_path)
+# Rename "all" CSV after completion
+if csv_all_final.exists():
+    csv_all_final.unlink()
+csv_all_tmp.rename(csv_all_final)
 
-print(f"CSV renamed to: {final_csv_path}")
+print(f"CSV (all) renamed to: {csv_all_final}")

scripts/coyote_protector_xtc_gui_ready_test/merge_crystals_data.py

@@ -31,7 +31,7 @@
 results_csv_dir = Path(f"run_{run_number}/results_csv")
 results_csv_dir = Path("results_csv")
 event_data_csv = results_csv_dir / "event_data.csv"
-measurements_csv = results_csv_dir / "measurements_complete.csv"
+measurements_csv = results_csv_dir / "measurements_above_threshold.csv"
 
 # Check if files exist
 if not event_data_csv.exists():