feat: update training script and config

This now reflects what we actually used during training :^)

model_research/nina.yaml

@@ -1,20 +1,19 @@
-path: C:\Users\benja\Documents\datasets\nina_yolo
-
+path: path/to/dataset # change this
 
 # These are relative to the path above
-train: obj_train_data
-val: obj_train_data
+train: train.txt
+val: val.txt
 test:
 
-nc: 9
-names: [
-  "Gjedde",
-  "Gullbust",
-  "Rumpetroll",
-  "Stingsild",
-  "Ørekyt",
-  "Abbor",
-  "Brasme",
-  "Mort",
-  "Vederbuk"
-]
+names:
+  0: Gjedde
+  1: Gullbust
+  2: Rumpetroll
+  3: Stingsild
+  4: Ørekyt
+  5: Abbor
+  6: Brasme
+  7: Mort
+  8: Vederbuk
+  9: Frosk
+  10: "Annen Fisk"

model_research/train.py

@@ -5,19 +5,44 @@
 # Use if you want to debug
 # os.environ["CUDA_LAUNCH_BLOCKING"] = "1"
 
-if __name__ == "__main__":
-    ultralytics.checks()
+
+def train(resume: bool) -> None:
+    """Train the model.
+
+    Args:
+        resume: If True, resume training from last checkpoint.
+    """
+    # Initialize with starting weights
     model = YOLO("yolov8s.pt")
+
+    # Train
     model.train(
-        data="nina_new.yaml",
-        epochs=100,
+        resume=resume,
+        data="nina.yaml",
+        epochs=120,
         val=True,
-        batch=16,
+        batch=8,
         imgsz=640,
-        device=0,
-        half=True,
-        workers=8,
+        device=None,
+        close_mosaic=10,
+        lr0=0.001,
+        lrf=0.01,
+        weight_decay=0.001,
+        degrees=10,
+        scale=0.6,
+        perspective=0.0005,
+        flipud=0.01,
+        hsv_h=0.2,
+        hsv_s=0.7,
+        hsv_v=0.7,
         v5loader=True,
-    )  # train the model
+        workers=16,
+    )
+
+
+if __name__ == "__main__":
+    # Perform checks
+    ultralytics.checks()
 
-    # model.val(data="brackish.yaml", batch_size=8)  # test the model
+    # Start/resume training
+    train(resume=False)