From 0274e954be7c2120ecdecea2092798aac59be9de Mon Sep 17 00:00:00 2001 From: Xiao Furen Date: Wed, 26 Aug 2026 22:36:07 +0800 Subject: [PATCH] refactor(core): improve cylinder parameter snapping and optimization logic Refactor the cylinder parameter selection and optimization process to improve accuracy and robustness. - Implement `snap_to_discrete_values_xfr` using a KDTree for efficient mapping of continuous diameter and length values to a predefined set of discrete points. - Update `objective_function_xfr` to use the new snapping mechanism and introduce a weighted loss component for diameter and length. - Adjust PSO optimization bounds and search ranges in `run_pso_torch_xfr` to better align with image dimensions and anatomical constraints. - Refine scoring logic in `cl_score_torch_xfr` with updated penalty weights for overlaps and out-of-bone voxels. - Update `config/constant.py` with new allowed diameter and length ranges. - Improve `imaging/preprocessing.py` by making `PROGRESS_FILE` a parameter to allow per-output-directory progress tracking. - Update `xfr_debug.py` with improved error handling and directory paths for batch processing. --- .gitignore | 4 +- .kilo/agents/data.md | 28 + .vscode/settings.json | 4 +- config/constant.py | 16 +- core/cylinder.py | 51 +- core/objective.py | 12 +- core/optimizer.py | 51 +- core/scoring.py | 13 +- imaging/preprocessing.py | 12 +- imaging/segmentation.py | 2 +- progress.json | 15175 +++++++++++++++++++++++++++++++++++++ xfr_debug.py | 52 +- xfr_preprocess.py | 2 +- 13 files changed, 15357 insertions(+), 65 deletions(-) create mode 100644 .kilo/agents/data.md diff --git a/.gitignore b/.gitignore index 64d49ae..64c415c 100644 --- a/.gitignore +++ b/.gitignore @@ -213,4 +213,6 @@ marimo/_lsp/ __marimo__/ # Streamlit -.streamlit/secrets.toml \ No newline at end of file +.streamlit/secrets.toml + +progress.json diff --git a/.kilo/agents/data.md b/.kilo/agents/data.md new file mode 100644 index 0000000..deae2e8 --- /dev/null +++ b/.kilo/agents/data.md @@ -0,0 +1,28 @@ +--- +mode: primary +description: Run notebook-first data analysis by appending and executing cells + for each request. +options: + displayName: Data + id: data +requirements: + skills: + - data-investigation + vscode_extensions: + - name: Jupyter + id: ms-toolsai.jupyter +color: "#2563EB" +--- + +You are Kilo, a notebook-first data analysis agent. Use an active Jupyter notebook as the working surface. + +Guidelines: +- If no notebook is active, create a uniquely named, descriptive `.ipynb` in the current workspace folder +- Use the dedicated notebook tools to create, read, edit, and execute; prefer these tools over other methods like MCP tools and manual raw JSON editing +- Confirm Jupyter and kernel readiness through the first requested notebook execution; only notify the user if they need to select or configure a kernel before work can continue +- For every user request, append at least one focused code cell and execute it +- Preserve notebook history: do not modify or delete existing cells unless explicitly asked; after failures, append diagnostic or corrected cells +- Keep substantive data work and supporting evidence in the notebook +- Avoid changing non-notebook files unless explicitly requested or necessary to complete the task +- Inspect cell output before answering, and keep notebook outputs and final summaries concise +- Never claim execution when a notebook cell did not run diff --git a/.vscode/settings.json b/.vscode/settings.json index 734461b..f9c24fe 100644 --- a/.vscode/settings.json +++ b/.vscode/settings.json @@ -1,5 +1,7 @@ { "python.analysis.extraPaths": [ "${workspaceFolder}" - ] + ], + "python-envs.defaultEnvManager": "ms-python.python:conda", + "python-envs.defaultPackageManager": "ms-python.python:conda" } \ No newline at end of file diff --git a/config/constant.py b/config/constant.py index e151d08..9641f2c 100644 --- a/config/constant.py +++ b/config/constant.py @@ -13,16 +13,26 @@ LABEL_MAP = { 20: "L1", 21: "L2", 22: "L3", 23: "L4", 24: "L5" } ALLOWED_DIAMETERS = [ - 3.5, - 4.0, + # 3.5, + # 4.0, 4.5, 5.0, + 5.5, + 6.0, + 6.5, + # 7.0, + # 7.5, ] ALLOWED_LENGTHS = [ + 25, + 30, 35, 40, 45, - 50, + # 50, + # 60, + # 70, + # 80, ] OVERLAP_THRESH = 0.50 DEFAULT_SPACING = [0.5, 0.5, 0.5] \ No newline at end of file diff --git a/core/cylinder.py b/core/cylinder.py index 7606f82..19b43c7 100644 --- a/core/cylinder.py +++ b/core/cylinder.py @@ -1,5 +1,9 @@ + +from scipy.spatial import KDTree + import torch import numpy as np + from config.constant import ALLOWED_DIAMETERS, ALLOWED_LENGTHS def create_coordinate_grid( @@ -38,7 +42,52 @@ def snap_to_discrete_values(diameter_raw, length_raw): return diameter_discrete, length_discrete -def round_down_to_discrete_values(diameter_raw, length_raw): +points = ( + (4.5, 25), + (4.5, 30), + (4.5, 35), + + (5.0, 30), + (5.0, 35), + (5.0, 40), + + (5.5, 30), + (5.5, 35), + (5.5, 40), + (5.5, 45), + (5.5, 50), + + (6.0, 35), + (6.0, 40), + (6.0, 45), + (6.0, 50), + (6.0, 55), + + (6.5, 35), + (6.5, 40), + (6.5, 45), + (6.5, 50), + (6.5, 55), + + (7.0, 35), + (7.0, 40), + (7.0, 45), + (7.0, 50), + + (7.5, 60), + (7.5, 70), + (7.5, 80), +) + +tree = KDTree(points) + +def snap_to_discrete_values_xfr(diameter_raw, length_raw): + return snap_to_discrete_values(diameter_raw, length_raw) + + distance, index = tree.query((diameter_raw, length_raw)) + return points[index][0], points[index][1] + +def round_down_to_discrete_values_xfr(diameter_raw, length_raw): """ 將連續值映射到小於等於該值的最接近允許離散值 (向下取整) diff --git a/core/objective.py b/core/objective.py index 2e5ee3b..cf15d9e 100644 --- a/core/objective.py +++ b/core/objective.py @@ -5,7 +5,7 @@ from scipy.ndimage import map_coordinates import numpy as np import torch -from core.cylinder import generate_cylinder_n_torch, generate_cylinder_o_torch, snap_to_discrete_values, generate_cylinder_tip_torch +from core.cylinder import generate_cylinder_n_torch, generate_cylinder_o_torch, snap_to_discrete_values, generate_cylinder_tip_torch, snap_to_discrete_values_xfr from core.intersection import center_line_intersections_torch from core.scoring import cl_score_torch, cl_score_torch_xfr @@ -138,11 +138,14 @@ def objective_function_xfr(params: list[float], y_indices) -> float: # 將連續值轉換為離散值 # diameter_discrete, length_discrete = snap_to_discrete_values(diameter_raw, length_raw) - diameter_discrete, length_discrete = diameter_raw, length_raw + diameter_discrete, length_discrete = snap_to_discrete_values_xfr(diameter_raw, length_raw) + + diameter_loss = .9*diameter_discrete + .1*diameter_raw + length_loss = .9* length_discrete + .1* length_raw loss = cylinder_circle_line_intersection_loss_deductions_torch( - diameter_discrete, - length_discrete, + diameter_loss, + length_loss, position_params, image2_shape, cortical_tensor, @@ -164,7 +167,6 @@ def objective_function(params: list[float]) -> float: # 將連續值轉換為離散值 diameter_discrete, length_discrete = snap_to_discrete_values(diameter_raw, length_raw) - # diameter_discrete, length_discrete = diameter_raw, length_raw loss = cylinder_circle_line_intersection_loss_deductions_torch( diameter_discrete, diff --git a/core/optimizer.py b/core/optimizer.py index 0a995b6..eea5f7b 100644 --- a/core/optimizer.py +++ b/core/optimizer.py @@ -7,13 +7,15 @@ from config.constant import ALLOWED_DIAMETERS, ALLOWED_LENGTHS from core.objective import objective_function, objective_function_xfr from pyswarm import pso import core.objective # <--- 加入這行，讓我們可以直接操作 objective 模組 -from core.cylinder import generate_cylinder_n_torch, snap_to_discrete_values, create_coordinate_grid, round_down_to_discrete_values +from core.cylinder import generate_cylinder_n_torch, snap_to_discrete_values, create_coordinate_grid, snap_to_discrete_values_xfr from core.scoring import compute_overlap_ratio_from_cylinder_mask, is_solution_ok from config.constant import OVERLAP_THRESH from visualization.res_plot_3d import res_plt_2_torch def get_first_nonzero_y(arr): + OUTSIDE_VALUE = -100 + # 1. Create a boolean mask where elements are non-zero mask = arr != 0 @@ -25,9 +27,10 @@ def get_first_nonzero_y(arr): has_nonzero = np.any(mask, axis=1) # 4. Replace indices where there were no non-zeros with a sentinel value (e.g., -1) - y_indices = np.where(has_nonzero, y_indices, -1) + y_indices = np.where(has_nonzero, y_indices, OUTSIDE_VALUE) - y_indices = np.where(y_indices > arr.shape[1] * .4, -1, y_indices) + y_indices = np.where(y_indices < arr.shape[1] * .1, OUTSIDE_VALUE, y_indices) + y_indices = np.where(y_indices > arr.shape[1] * .4, OUTSIDE_VALUE, y_indices) return y_indices.astype(np.float32) @@ -115,13 +118,16 @@ def run_pso_torch_xfr( # flat_min_index = np.argmin(y_indices) # z_border, x_border = np.unravel_index(flat_min_index, y_indices.shape) - x_with_nonzero = np.where(np.any(image2_array[:,9,:] != 0, axis=0))[0] + x_with_nonzero = np.where(np.any(image2_array[:,image_shape[1]//10,:] != 0, axis=0))[0] x1 = x_with_nonzero[0] x2 = x_with_nonzero[-1] + # print(x1,x2) + # exit() + x_mid = (x1+x2)/2 - x1 = x_mid-9 - x2 = x_mid+9 + x1 = x_mid-image_shape[2]*.1 + x2 = x_mid+image_shape[2]*.1 z_sum = np.sum(image2_array, axis=(1, 2)) z_with_nonzero = np.where(z_sum > 0)[0] @@ -141,19 +147,20 @@ def run_pso_torch_xfr( # 設定基本的 bounds if CBT == True: - z_bounds = (0, image_shape[0] / 2) + # z_bounds = (0, image_shape[0]-1) # z_bounds = (z1, (z1+z2)/2) - x_bounds_right = (image_shape[2]/2 + image_shape[2]/10, image_shape[2] - 1) - x_bounds_left = (0, image_shape[2]/2 - image_shape[2]/10 - 1) + z_bounds = (.1*image_shape[0], .8*image_shape[0]) + # x_bounds_right = (image_shape[2]/2 + image_shape[2]/10, image_shape[2] - 1) + # x_bounds_left = (0, image_shape[2]/2 - image_shape[2]/10 - 1) x_bounds_right = (x2, image_shape[2]*.9) x_bounds_left = (image_shape[2]*.1, x1) # azimuth_bounds_l = ((95-azi), (145-azi)) # azimuth_bounds_r = ((50-azi), (85-azi)) # altitude_bounds = ((60-alt), (75-alt)) - azimuth_bounds_l = ((95-azi), (105-azi)) - azimuth_bounds_r = ((75-azi), (85-azi)) - altitude_bounds = ((55-alt), (70-alt)) + azimuth_bounds_l = ((98-azi), (120-azi)) + azimuth_bounds_r = ((60-azi), (82-azi)) + altitude_bounds = ((60-alt), (70-alt)) else: z_bounds = (0, image_shape[0] - 1) @@ -173,7 +180,7 @@ def run_pso_torch_xfr( """ if optimize_size: # d, L = snap_to_discrete_values(pos[5], pos[6]) - d, L = round_down_to_discrete_values(pos[5], pos[6]) + d, L = snap_to_discrete_values_xfr(pos[5], pos[6]) params_5 = pos[:5] else: d, L = diameter, length @@ -221,7 +228,7 @@ def run_pso_torch_xfr( lb_r = [z_bounds[0], y_bounds[0], x_bounds_right[0], azimuth_bounds_r[0], altitude_bounds[0]] ub_r = [z_bounds[1], y_bounds[1], x_bounds_right[1], azimuth_bounds_r[1], altitude_bounds[1]] - if debug: + if True or debug: print(lb_l) print(ub_l) print(lb_r) @@ -233,7 +240,7 @@ def run_pso_torch_xfr( best_position_r = None # Left side optimization - print("\n=== 左側 ===") + print(f"\n=== {label_str} 左側 ===") kwargs = {'y_indices': y_indices} position_l, loss_l = pso(objective_function_xfr, lb_l, ub_l, @@ -299,7 +306,7 @@ def run_pso_torch_xfr( # retries += 1 # Right side optimization - print("\n=== 右側 ===") + print(f"\n=== {label_str} 右側 ===") position_r, loss_r = pso(objective_function_xfr, lb_r, ub_r, # ieqcons=[constraint_y], kwargs=kwargs, @@ -318,7 +325,7 @@ def run_pso_torch_xfr( if optimize_size: # diameter_r, length_r = snap_to_discrete_values(position_r[5], position_r[6]) - diameter_r, length_r = round_down_to_discrete_values(position_r[5], position_r[6]) + diameter_r, length_r = snap_to_discrete_values_xfr(position_r[5], position_r[6]) print(f"[RIGHT] Position: {position_r[:5]}") print(f"[RIGHT] Diameter: {diameter_r} mm (raw: {position_r[5]:.2f})") print(f"[RIGHT] Length: {length_r} mm (raw: {position_r[6]:.2f})") @@ -376,7 +383,7 @@ def run_pso_torch_xfr( final_diameter_r = best_position_r[5] final_length_r = best_position_r[6] - print(f"\n=== 最終結果 ===") + print(f"\n=== {label_str} 最終結果 ===") print(f"Left - Diameter: {final_diameter_l} mm, Length: {final_length_l} mm") print(f"Right - Diameter: {final_diameter_r} mm, Length: {final_length_r} mm") else: @@ -520,7 +527,7 @@ def run_pso_torch( """ if optimize_size: # d, L = snap_to_discrete_values(pos[5], pos[6]) - d, L = round_down_to_discrete_values(pos[5], pos[6]) + d, L = snap_to_discrete_values_xfr(pos[5], pos[6]) params_5 = pos[:5] else: d, L = diameter, length @@ -643,7 +650,7 @@ def run_pso_torch( if optimize_size: # diameter_r, length_r = snap_to_discrete_values(position_r[5], position_r[6]) - diameter_r, length_r = round_down_to_discrete_values(position_r[5], position_r[6]) + diameter_r, length_r = snap_to_discrete_values_xfr(position_r[5], position_r[6]) print(f"[RIGHT] Position: {position_r[:5]}") print(f"[RIGHT] Diameter: {diameter_r} mm (raw: {position_r[5]:.2f})") print(f"[RIGHT] Length: {length_r} mm (raw: {position_r[6]:.2f})") @@ -836,7 +843,7 @@ def run_de_torch( def eval_overlap_from_position(pos, side: str, optimize_size: bool, spine_tensor: torch.Tensor, image_shape, spacing): if optimize_size: # d, L = snap_to_discrete_values(pos[5], pos[6]) - d, L = round_down_to_discrete_values(pos[5], pos[6]) + d, L = snap_to_discrete_values_xfr(pos[5], pos[6]) params_5 = pos[:5] else: d, L = diameter, length @@ -1015,7 +1022,7 @@ def run_nm_torch( def eval_overlap_from_position(pos, side: str, optimize_size: bool, spine_tensor: torch.Tensor, image_shape, spacing): if optimize_size: # d, L = snap_to_discrete_values(pos[5], pos[6]) - d, L = round_down_to_discrete_values(pos[5], pos[6]) + d, L = snap_to_discrete_values_xfr(pos[5], pos[6]) params_5 = pos[:5] else: d, L = diameter, length diff --git a/core/scoring.py b/core/scoring.py index 8b0ef65..14d39c1 100644 --- a/core/scoring.py +++ b/core/scoring.py @@ -23,9 +23,8 @@ def cl_score_torch_xfr( in_bone= ((spine_tensor == 1) & (cylinder_torch == 1)).sum().item() not_in_bone= ((spine_tensor == 0) & (cylinder_torch == 1)).sum().item() - # if cyl_total == 0: - # return float(1000*1000) - # return float(1e9) # 極差的情況 + if cyl_total == 0: + return float(1e9) # 極差的情況 overlap_ratio = overlap / cyl_total @@ -37,10 +36,10 @@ def cl_score_torch_xfr( # if in_bone == 0: # return float(not_in_bone*200) - score += overlap*30 - score += in_bone*10 - score -= not_in_bone*1000 - score -= null_vox2*1000 + score += 10 * in_bone # 10 實在太低 + score += 100 * overlap + score -= 2000 * max(0, not_in_bone-10) + score -= 1000 * max(0, null_vox2-10) return float(-score) diff --git a/imaging/preprocessing.py b/imaging/preprocessing.py index 7a293b3..0a5e69e 100644 --- a/imaging/preprocessing.py +++ b/imaging/preprocessing.py @@ -8,15 +8,15 @@ import glob from config.constant import LABEL_MAP from imaging.nifti_io import sitk_to_nibabel, nibabel_to_sitk -PROGRESS_FILE = "progress.json" -def load_progress(): + +def load_progress(PROGRESS_FILE): if os.path.exists(PROGRESS_FILE): with open(PROGRESS_FILE, "r") as f: return json.load(f) return {} -def save_progress(progress): +def save_progress(progress, PROGRESS_FILE): with open(PROGRESS_FILE, "w") as f: json.dump(progress, f, indent=2) @@ -73,7 +73,9 @@ def process_dataset(image_dir, label_dir, output_dir, labels_to_process=None): total_files = len(image_files) print(f"Total files: {total_files}") - progress = load_progress() + PROGRESS_FILE = os.path.join(output_dir, "progress.json") + + progress = load_progress(PROGRESS_FILE) all_file_summary = [] for idx, image_path in enumerate(image_files, 1): @@ -119,7 +121,7 @@ def process_dataset(image_dir, label_dir, output_dir, labels_to_process=None): "processed_labels": result["processed_labels"], "missing_labels": result["missing_labels"] } - save_progress(progress) + save_progress(progress, PROGRESS_FILE) print(f"[{idx}/{total_files}] Finished: {file_name} | Missing labels: {result['missing_labels'] or 'None'}") diff --git a/imaging/segmentation.py b/imaging/segmentation.py index 784f775..0d68778 100644 --- a/imaging/segmentation.py +++ b/imaging/segmentation.py @@ -35,7 +35,7 @@ def seg_bone(n, name, resampled_sitk_img, resampled_sitk_lbl, output_base=None, # 2. 獲取所有連通區域 # 連通區域濾波器會將 binary_mask 中的不同物體標記為 1, 2, 3... - cc_image = sitk.ConnectedComponent(binary_mask) + cc_image = sitk.ConnectedComponent(binary_mask, True) #fullyConnected # 3. 根據區域大小（像素/體積）重新標記 # RelabelComponent 會按大小排序，最大的物體標籤會被設為 1 diff --git a/progress.json b/progress.json index 4fb56ba..88913a4 100644 --- a/progress.json +++ b/progress.json @@ -1621,5 +1621,15180 @@ 23 ], "missing_labels": [] + }, + "1.3.6.1.4.1.9328.50.4.0109": { + "finished": true, + "processed_labels": [ + 16, + 17, + 18, + 19, + 20, + 21, + 22, + 23, + 24 + ], + "missing_labels": [] + }, + "1.3.6.1.4.1.9328.50.4.0110": { + "finished": true, + "processed_labels": [ + 14, + 15, + 16, + 17, + 18, + 19, + 20, + 21, + 22, + 23 + ], + "missing_labels": [] + }, + "1.3.6.1.4.1.9328.50.4.0111": { + "finished": true, + "processed_labels": [ + 15, + 16, + 17, + 18, + 19, + 20, + 21, + 22, + 23, + 24 + ], + "missing_labels": [] + }, + "1.3.6.1.4.1.9328.50.4.0112": { + "finished": true, + "processed_labels": [ + 14, + 15, + 16, + 17, + 18, 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'/mnt/1248/open2/cyrou/azimuth_rotation' +tilt_contour_dir = '/mnt/1248/open2/cyrou/tilt_contour' Output_dir = '/mnt/1248/open/cyrou/Output' def get_device(gpu_id=None): @@ -95,7 +95,7 @@ def debug_pso(volume_id, level): ) best_l, loss_l, best_r, loss_r, total_time = run_pso_torch_xfr( - label_str=level, + label_str=f'{volume_id} {level}', image1_path=cortical_path, image2_path=binary_path, image3_path=roi_path, @@ -121,21 +121,37 @@ def main(): # process_volume(volume_id, level) # exit() - for volume_id in ( - '1.3.6.1.4.1.9328.50.4.0001', - # '1.3.6.1.4.1.9328.50.4.0002', - # '1.3.6.1.4.1.9328.50.4.0003', - # '1.3.6.1.4.1.9328.50.4.0004', - # '1.3.6.1.4.1.9328.50.4.0005', - # '1.3.6.1.4.1.9328.50.4.0006', - ): - # for volume_id in sorted(os.listdir(standardized_dir)): - # debug_orientation(volume_id, level) - for level in ('L1', 'L2', 'L3', 'L4', 'L5'): - # debug_orientation(volume_id, level) - debug_pso(volume_id, level) + MAX_SUCCESSFUL_VOLUMES = 100 + number_of_successful_volumes = 0 - exit() + # for volume_id in ( + # '1.3.6.1.4.1.9328.50.4.0001', + # '1.3.6.1.4.1.9328.50.4.0002', + # '1.3.6.1.4.1.9328.50.4.0003', + # '1.3.6.1.4.1.9328.50.4.0004', + # '1.3.6.1.4.1.9328.50.4.0005', + # # '1.3.6.1.4.1.9328.50.4.0006', + # ): + + for volume_id in sorted(os.listdir(standardized_dir)): + # debug_orientation(volume_id, level) + error_flag = False + for level in ('L1', 'L2', 'L3', 'L4', 'L5'): + # for level in ('L5',): + # debug_orientation(volume_id, level) + try: + debug_pso(volume_id, level) + except Exception as e: + print(f'Error in {volume_id} {level}: {e}') + error_flag = True + continue + if not error_flag: + number_of_successful_volumes += 1 + + if number_of_successful_volumes >= MAX_SUCCESSFUL_VOLUMES: + break + + # exit() diff --git a/xfr_preprocess.py b/xfr_preprocess.py index 1aab0aa..32c6b5c 100644 --- a/xfr_preprocess.py +++ b/xfr_preprocess.py @@ -4,7 +4,7 @@ from imaging.preprocessing import process_dataset data_root = '/mnt/1220/Public/dataset/Spine/CTSpine1K/data/' label_root = '/mnt/1220/Public/dataset/Spine/CTSpine1K/label/' -output_dir = '/mnt/1248/open2/cyrou/CBT/Seg/Resample/standardized-xfr/' +output_dir = '/mnt/1248/open2/cyrou/CBT/Seg/Resample/standardized-xfr-2/' label_map = { 'colon': 'conlon',