(CHORE)[config[: Refine configuration for model weights, sample data, and UI state

- Centralized key configuration for Streamlit session state persistence (`KEEP_KEYS`), ensuring important UI context is retained after resets.
- Set `TARGET_LEN` for standardized spectrum preprocessing length.
- Defined `SAMPLE_DATA_DIR` using pathlib for robust path handling.
- Improved `MODEL_WEIGHTS_DIR` logic: checks for environment variable `WEIGHTS_DIR`, falls back to `model_weights` directory if present, otherwise defaults to `outputs`.
- Added clear label mapping (`LABEL_MAP`) for model output classes: "Stable (Unweathered)" and "Weathered (Degraded)".
- Enhanced maintainability and clarity of global configuration for

config.py

@@ -1,43 +1,20 @@
-from pathlib import Path
-import os
-from models.figure2_cnn import Figure2CNN
-from models.resnet_cnn import ResNet1D
-
-KEEP_KEYS = {
-    # ==global UI context we want to keep after "Reset"==
-    "model_select",     # sidebar model key
-    "input_mode",       # radio for Upload|Sample
-    "uploader_version",  # version counter for file uploader
-    "input_registry",   # radio controlling Upload vs Sample
-}
-
-TARGET_LEN = 500
-SAMPLE_DATA_DIR = Path("sample_data")
-
-MODEL_WEIGHTS_DIR = (
-    os.getenv("WEIGHTS_DIR")
-    or ("model_weights" if os.path.isdir("model_weights") else "outputs")
-)
-
-# Model configuration
-MODEL_CONFIG = {
-    "Figure2CNN (Baseline)": {
-        "class": Figure2CNN,
-        "path": f"{MODEL_WEIGHTS_DIR}/figure2_model.pth",
-        "emoji": "",
-        "description": "Baseline CNN with standard filters",
-        "accuracy": "94.80%",
-        "f1": "94.30%"
-    },
-    "ResNet1D (Advanced)": {
-        "class": ResNet1D,
-        "path": f"{MODEL_WEIGHTS_DIR}/resnet_model.pth",
-        "emoji": "",
-        "description": "Residual CNN with deeper feature learning",
-        "accuracy": "96.20%",
-        "f1": "95.90%"
-    }
-}
-
-# ==Label mapping==
-LABEL_MAP = {0: "Stable (Unweathered)", 1: "Weathered (Degraded)"}
+from pathlib import Path
+import os
+
+KEEP_KEYS = {
+    # ==global UI context we want to keep after "Reset"==
+    "model_select",  # sidebar model key
+    "input_mode",  # radio for Upload|Sample
+    "uploader_version",  # version counter for file uploader
+    "input_registry",  # radio controlling Upload vs Sample
+}
+
+TARGET_LEN = 500
+SAMPLE_DATA_DIR = Path("sample_data")
+
+MODEL_WEIGHTS_DIR = os.getenv("WEIGHTS_DIR") or (
+    "model_weights" if os.path.isdir("model_weights") else "outputs"
+)
+
+# ==Label mapping==
+LABEL_MAP = {0: "Stable (Unweathered)", 1: "Weathered (Degraded)"}