Krishnan RamachandranandClaude Sonnet 4.6
e8e7ad545c
- Auto-expand node width to 700px min and recalculate height after all thumbnails load (double-rAF) so content no longer overflows the node - Add mouse wheel zoom (0.5x–10x) in fullscreen viewer with smooth transition; resets on image navigation - Fix image ordering: swap Python loop and JS index formula to mode-outer/ camera-inner so arrows navigate all cameras per mode, not all modes per camera - Fix viewer title labels (mode/cam were swapped after reorder) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
232 lines
7.9 KiB
Python
232 lines
7.9 KiB
Python
import subprocess
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import sys
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import time
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import os
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import json
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from uuid import uuid4
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import folder_paths
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# Path to the agnirt binary bundled with this plugin
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PLUGIN_DIR = os.path.dirname(os.path.abspath(__file__))
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if sys.platform == "win32":
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AGNIRT_DIR = os.path.join(PLUGIN_DIR, "bin", "win-x64")
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AGNIRT_BIN = os.path.join(AGNIRT_DIR, "agnirt.exe")
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else:
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AGNIRT_DIR = os.path.join(PLUGIN_DIR, "bin", "linux-x64")
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AGNIRT_BIN = os.path.join(AGNIRT_DIR, "agnirt")
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# agnirt output segment names (must match what the binary emits)
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CAMERAS = ["perspective", "front", "right", "left"]
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MODES = ["pathtracing", "wireframe", "geometry-analysis", "sliver-triangles"]
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# Human-readable display labels for the carousel
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CAMERA_DISPLAY = {
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"perspective": "Perspective",
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"front": "Front",
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"right": "Right",
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"left": "Left",
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}
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MODE_DISPLAY = {
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"pathtracing": "Path Trace",
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"wireframe": "Wireframe",
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"geometry-analysis": "Geo Analysis",
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"sliver-triangles": "Sliver Tri",
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}
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def _parse_audit_log(log_path, total_faces):
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"""
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Parse audit_log.json and extract mesh statistics.
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Args:
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log_path: Path to audit_log.json file
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total_faces: Total face count (used to calculate degenerate % if needed)
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Returns:
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Dict with keys: scene, geometry, quality_metrics
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Returns None if file not found or parse error
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"""
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try:
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with open(log_path, 'r') as f:
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data = json.load(f)
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except (FileNotFoundError, json.JSONDecodeError) as e:
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print(f"Warning: Could not parse audit_log.json: {e}")
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return None
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try:
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# Extract scene metadata
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asset_name = data.get("asset", {}).get("name", "Unknown")
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timestamp = data.get("asset", {}).get("timestamp", "N/A")
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# Extract geometry stats
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scene = data.get("scene_stats", {})
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edge_count = scene.get("edge_count", 0)
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face_count = scene.get("face_count", 0)
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vertex_count = scene.get("vertex_count", 0)
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# Extract validation metrics
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validation = data.get("validation", {})
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degen_count = validation.get("degenerate_triangles", 0)
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inverted_count = validation.get("inverted_triangles", 0)
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sliver_data = validation.get("sliver_triangles", {})
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sliver_pct = sliver_data.get("percentage", 0.0) if isinstance(sliver_data, dict) else 0.0
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# Calculate percentages (avoid division by zero)
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degen_pct = (degen_count / face_count * 100) if face_count > 0 else 0.0
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inverted_pct = (inverted_count / face_count * 100) if face_count > 0 else 0.0
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return {
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"scene": {
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"name": asset_name,
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"timestamp": timestamp
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},
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"geometry": {
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"edge_count": edge_count,
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"face_count": face_count,
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"vertex_count": vertex_count
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},
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"quality_metrics": {
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"degenerate_triangles_pct": round(degen_pct, 2),
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"sliver_triangles_pct": round(sliver_pct, 2),
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"inverted_triangles_pct": round(inverted_pct, 2)
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}
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}
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except Exception as e:
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print(f"Warning: Error extracting stats from audit_log.json: {e}")
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return None
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class PulseMeshAudit:
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CATEGORY = "Pulse/MeshAudit"
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RETURN_TYPES = ()
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OUTPUT_NODE = True
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"file_path": ("STRING", {"default": ""}),
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}
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}
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FUNCTION = "execute"
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def execute(self, file_path):
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# Resolve relative paths — check output directory first, then input directory
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if not os.path.isabs(file_path):
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output_candidate = os.path.join(folder_paths.get_output_directory(), file_path)
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input_candidate = os.path.join(folder_paths.get_input_directory(), file_path)
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if os.path.isfile(output_candidate):
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file_path = output_candidate
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else:
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file_path = input_candidate
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if not os.path.isfile(file_path):
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raise FileNotFoundError(f"Mesh file not found: {file_path}")
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# Output base: agnirt appends _{mode}_{camera}.png automatically
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run_id = str(uuid4())[:8]
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temp_dir = folder_paths.get_temp_directory()
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output_base = os.path.join(temp_dir, f"ma_{run_id}.png")
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# Need lib dir on LD_LIBRARY_PATH for libcrt_vulkan.so
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env = os.environ.copy()
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prev_ldpath = env.get("LD_LIBRARY_PATH", "")
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env["LD_LIBRARY_PATH"] = f"{AGNIRT_DIR}:{prev_ldpath}" if prev_ldpath else AGNIRT_DIR
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print("[MeshAudit] Starting agnirt...")
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proc = subprocess.Popen(
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[
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AGNIRT_BIN, "vulkan", file_path,
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"-headless",
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"-shading-mode", "all",
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"--camera", "perspective", "front", "right", "left",
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"-env", "../../assets/sunny_rose_garden_4k.exr",
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"-o", output_base,
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],
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cwd=AGNIRT_DIR, # agnirt reads assets/ relative to cwd
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env=env,
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stdout=subprocess.PIPE,
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stderr=subprocess.PIPE,
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text=True,
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)
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stdout_lines = []
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for line in proc.stdout:
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line = line.rstrip()
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stdout_lines.append(line)
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print(f"[agnirt] {line}", flush=True)
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proc.wait()
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stderr_out = proc.stderr.read()
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if proc.returncode != 0:
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raise RuntimeError(
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f"agnirt failed (rc={proc.returncode}):\n{stderr_out[-1000:]}"
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)
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# Expose result-like interface for downstream code
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class _Result:
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stdout = "\n".join(stdout_lines)
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result = _Result()
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# Build image list + carousel labels in camera-outer, mode-inner order
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images = []
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labels = []
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for mode in MODES:
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for cam in CAMERAS:
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filename = f"ma_{run_id}_{mode}_{cam}.png"
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full_path = os.path.join(temp_dir, filename)
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if not os.path.isfile(full_path):
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raise FileNotFoundError(
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f"Expected agnirt output missing: {filename}\n"
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f"agnirt stdout: {result.stdout[-500:]}"
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)
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images.append({"filename": filename, "subfolder": "", "type": "temp"})
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labels.append(f"{CAMERA_DISPLAY[cam]} • {MODE_DISPLAY[mode]}")
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# Locate and parse audit_log.json if available
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# agnirt creates audit_log_<name>_<timestamp>.json, find the latest one
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asset_stats = None
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import glob
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# Try multiple possible locations for audit_log
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possible_temps = [
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temp_dir,
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"/home/krishnan/ai_lab/apps/ComfyUI/temp",
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os.path.expanduser("~/ai_lab/apps/ComfyUI/temp"),
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]
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audit_log_path = None
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for search_dir in possible_temps:
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if os.path.isdir(search_dir):
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audit_logs = glob.glob(os.path.join(search_dir, "audit_log_*.json"))
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if audit_logs:
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audit_log_path = max(audit_logs, key=os.path.getctime)
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break
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if audit_log_path:
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print(f"[MeshAudit] Found audit log: {audit_log_path}")
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asset_stats = _parse_audit_log(audit_log_path, len(MODES) * len(CAMERAS))
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if asset_stats:
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print(f"[MeshAudit] Parsed stats: {asset_stats['scene']['name']}")
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else:
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print(f"[MeshAudit] Could not find audit_log in any temp directory")
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response = {
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"ui": {
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"images": images,
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"mesh_audit_carousel": [{"labels": labels}],
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}
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}
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# Add asset_stats if parsing succeeded
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if asset_stats:
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response["ui"]["asset_stats"] = [asset_stats]
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return response
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@classmethod
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def IS_CHANGED(cls, **kwargs):
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return time.time()
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