New stuff (#9)

* fix: update Google Drive file ID for model download

* fix: update run function to return empty arrays on error

* refactor: update Config class to use Path for input and output settings

* fix: convert output_dir and model_path to string in detection method

* fix: convert input_image to string before loading in run function

* fix: update write_json function to use Any type for content parameter

* fix: simplify line coefficient computation in LeastSquaresSolution

* fix: update drawing import to use LineDrawing for line visualization

* fix: update import statement for euclidean_distance in Line class

* fix: return float type for euclidean_distance function result

* fix: ensure boolean type for good_alignment in find_detections return value

* refactor: remove unused detection methods and related code

Author: tuke307

tree-disk-api/src/config/preparation.py

@@ -15,7 +15,7 @@ def download_u2net_model():
     """
     Download the model from Google Drive.
     """
-    file_id = "1ao1ovG1Qtx4b7EoskHXmi2E9rp5CHLcZ"
+    file_id = "10HXfiEMT4QapiRXMSSEJEAViRmRmSDUW"
     url = f"https://drive.google.com/uc?id={file_id}"
 
     logger.info(f"Downloading Google Drive file from: {url}")

tree-disk-pith/README.md

@@ -20,6 +20,7 @@ import treediskpith
 # Configure the analyzer
 treediskpith.configure(
     input_image="input/tree-disk4.png",
+    model_path="models/apd_dl.h5",
     save_results=True,
 )
 
@@ -35,24 +36,15 @@ treediskpith.configure(
 
 Basic usage:
 ```bash
-tree-disk-pith --input_image ./input/tree-disk3.png --new_shape 640 --debug
-```
-
-Save intermediate results:
-```bash
-tree-disk-pith --input_image ./input/tree-disk3.png --new_shape 640 --debug --method apd_pcl --save_results
+tree-disk-pith --input_image ./input/tree-disk3.png
 ```
 
 Advanced usage with custom parameters:
 ```bash
 tree-disk-pith \
     --input_image input/tree-disk3.png \
-    --cx 1204 \
-    --cy 1264 \
     --output_dir custom_output/ \
-    --sigma 4.0 \
-    --th_low 10 \
-    --th_high 25 \
+    --new_shape 640 \
     --save_results \
     --debug
 ```
@@ -63,12 +55,7 @@ tree-disk-pith \
 |----------|------|----------|---------|-------------|
 | `--input_image` | str | Yes | - | Input image file path |
 | `--output_dir` | str | Yes | - | Output directory path |
-| `--method` | str | No | apd | Detection method to use. Choices are apd, apd_pcl, or apd_dl |
 | `--model_path` | str | No | - | Path to the weights file (required if using apd_dl method) |
-| `--percent_lo` | float | No | 0.7 | percent_lo parameter for the algorithm |
-| `--st_w` | int | No | 3 | st_w parameter for the algorithm |
-| `--lo_w` | int | No | 3 | lo_w parameter for the algorithm |
-| `--st_sigma` | float | No | 1.2 | st_sigma parameter for the algorithm |
 | `--new_shape` | int | No | 0 | New shape for resizing the input image. If 0, no resizing is done |
 | `--debug` | flag | No | False | Enable debug mode to save intermediate images and outputs |
 | `--save_results` | flag | No | False | Save intermediate images, labelme and config file |
@@ -88,17 +75,17 @@ poetry install
 eval $(poetry env activate)
 ```
 
-1. Running tests:
+2. Running tests:
 ```bash
-poetry run pytest
+pytest
 ```
 
-1. fetch dataset
+3. fetch dataset
 ```bash
 python fetch_dataset.py
 ```
 
-1. Download pretrained model
+4. Download pretrained model
 ```bash
 python fetch_pretrained_model.py
 ```

tree-disk-pith/src/treediskpith/cli.py

@@ -17,29 +17,11 @@ def parse_arguments():
     parser.add_argument(
         "--output_dir", type=str, default=Config.output_dir, help="Output directory"
     )
-    parser.add_argument(
-        "--method",
-        type=str,
-        choices=["apd", "apd_pcl", "apd_dl"],
-        default=Config.method,
-        help="Method to use: 'apd', 'apd_pcl', or 'apd_dl'",
-    )
     parser.add_argument(
         "--model_path",
         type=str,
         default=Config.model_path,
-        help="Path to the weights file (required for method 'apd_dl')",
-    )
-    parser.add_argument(
-        "--percent_lo",
-        type=float,
-        default=Config.percent_lo,
-        help="percent_lo parameter",
-    )
-    parser.add_argument("--st_w", type=int, default=Config.st_w, help="st_w parameter")
-    parser.add_argument("--lo_w", type=int, default=Config.lo_w, help="lo_w parameter")
-    parser.add_argument(
-        "--st_sigma", type=float, default=Config.st_sigma, help="st_sigma parameter"
+        help="Path to the weights file",
     )
     parser.add_argument(
         "--new_shape",
@@ -62,11 +44,6 @@ def main():
     configure(
         input_image=args.input_image,
         output_dir=args.output_dir,
-        method=args.method,
-        percent_lo=args.percent_lo,
-        st_w=args.st_w,
-        lo_w=args.lo_w,
-        st_sigma=args.st_sigma,
         new_shape=args.new_shape,
         debug=args.debug,
         model_path=args.model_path,

tree-disk-pith/src/treediskpith/config.py

@@ -4,7 +4,6 @@
 import logging
 from typing import Any, Dict, Optional
 from datetime import datetime
-from .detection.detection_method import DetectionMethod
 
 from .utils.file_utils import ensure_directory
 
@@ -21,27 +20,17 @@ class Config:
     Attributes:
         input_image (str): Input image file path.
         output_dir (str): Output directory path.
-        method (Method): Detection method to use.
-        percent_lo (float): Percent_lo parameter for detection.
-        st_w (int): ST_W parameter for spatial filtering.
-        lo_w (int): LO_W parameter for local optimization.
-        st_sigma (float): ST_Sigma parameter for Gaussian filtering.
         new_shape (int): New shape for resizing the image.
         debug (bool): Enable debug mode for additional logging.
-        model_path (Optional[str]): Path to model file (required for 'apd_dl' method).
+        model_path (Optional[str]): Path to model file.
     """
 
     # -------------- Input/Output Settings ----------------
-    input_image: str = ""
-    output_dir: str = "./output/"
-    method: DetectionMethod = DetectionMethod.APD
-    model_path: Optional[str] = None
+    input_image: Optional[Path] = None
+    output_dir: Path = Path("./output/")
+    model_path: Optional[Path] = None
 
     # -------------- Processing Parameters ----------------
-    percent_lo: float = 0.1
-    st_w: int = 5
-    lo_w: int = 3
-    st_sigma: float = 1.0
     new_shape: int = 0
 
     # -------------- Operation Modes ----------------
@@ -60,8 +49,10 @@ def __post_init__(self):
                 self._change_history[field_name] = []
 
         # Validate method-specific requirements
-        if self.method == DetectionMethod.APD_DL and not self.model_path:
-            raise ValueError("model_path is required when using APD_DL method")
+        if not self.model_path:
+            logger.warning(
+                "model_path is not set yet. It is required for proper operation. Please configure it accordingly."
+            )
 
     def _validate_and_set_paths(self):
         """Validate and set all path-related fields."""
@@ -72,12 +63,12 @@ def _validate_and_set_paths(self):
                 raise ValueError(f"Input image file does not exist: {input_path}")
             if not input_path.is_file():
                 raise ValueError(f"Input image path is not a file: {input_path}")
-            self.input_image = str(input_path.resolve())
+            self.input_image = input_path.resolve()
 
         # Set up output directory
         output_path = Path(self.output_dir)
         try:
-            self.output_dir = str(ensure_directory(output_path))
+            self.output_dir = ensure_directory(output_path)
         except PermissionError:
             raise ValueError(
                 f"Cannot create output directory (permission denied): {output_path}"
@@ -92,7 +83,7 @@ def _validate_and_set_paths(self):
                 raise ValueError(f"Model file does not exist: {model_path}")
             if not model_path.is_file():
                 raise ValueError(f"Model path is not a file: {model_path}")
-            self.model_path = str(model_path.resolve())
+            self.model_path = model_path.resolve()
 
     def _log_change(self, param: str, old_value: Any, new_value: Any):
         """Log a parameter change with timestamp."""
@@ -124,15 +115,13 @@ def update(self, **kwargs):
 
             old_value = getattr(self, key)
             if old_value != new_value:
-                if key == "method":
-                    new_value = DetectionMethod(new_value)
                 setattr(self, key, new_value)
                 self._log_change(key, old_value, new_value)
 
         if needs_validation:
             self._validate_and_set_paths()
 
-    def get_change_history(self, param: str = None) -> Dict:
+    def get_change_history(self, param: Optional[str] = None) -> Dict:
         """
         Get change history for a specific parameter or all parameters.
 
@@ -151,11 +140,7 @@ def get_change_history(self, param: str = None) -> Dict:
     def to_dict(self) -> dict:
         """Convert configuration to dictionary, excluding internal fields."""
         return {
-            k: (
-                v.value
-                if isinstance(v, DetectionMethod)
-                else str(v) if isinstance(v, Path) else v
-            )
+            k: (str(v) if isinstance(v, Path) else v)
             for k, v in self.__dict__.items()
             if not k.startswith("_")
         }
@@ -186,9 +171,7 @@ def configure(**kwargs):
     Example:
         >>> configure(
         ...     input_image="sample.jpg",
-        ...     method="apd_dl",
         ...     model_path="model.pth",
-        ...     st_w=7
         ... )
     """
     config.update(**kwargs)