Latest web ui that support DefectFill and DefectDiffu model run simultaneusly

ArtiAgent - DefectDiffu/src/artiagent_orchestrator.py

@@ -271,7 +271,7 @@ class ArtiAgentOrchestrator:
     # ------------------------------------------------------------------
 
     def plan(self, product_description: str, image: np.ndarray,
-             defect_type: Optional[str] = None, max_defects: int = 3):
+             defect_type: Optional[str] = None, num_defects: int = 3):
         """Agent plans defects based on product knowledge."""
         print(f"\\n{'='*60}")
         print("[Agent] Step 1: Planning defects from product description...")
@@ -285,7 +285,7 @@ class ArtiAgentOrchestrator:
             image,
             money_manager=self.money_manager,
             target_defect_type=defect_type,
-            max_defects=max_defects
+            num_defects=num_defects
         )
 
         if plan is None:
@@ -543,7 +543,7 @@ class ArtiAgentOrchestrator:
     # ------------------------------------------------------------------
 
     def run(self, product_description: str, image_path: str,
-            caption: Optional[str] = None, max_defects: int = 3,
+            caption: Optional[str] = None, num_defects: int = 3,
             defect_type: Optional[str] = None) -> Dict:
         """Run the full agentic pipeline with DefectDiffu."""
         start_time = datetime.now()
@@ -558,10 +558,10 @@ class ArtiAgentOrchestrator:
 
         print(f"[Agent] Loaded image: {image.shape}")
 
-        plan = self.plan(product_description, image, defect_type=defect_type, max_defects=max_defects)
+        plan = self.plan(product_description, image, defect_type=defect_type, num_defects=num_defects)
 
         results = []
-        defects_to_process = plan.possible_defects[:max_defects]
+        defects_to_process = plan.possible_defects[:num_defects]
         print(f"[Agent] Processing top {len(defects_to_process)} of {len(plan.possible_defects)} planned defects")
 
         for i, defect_plan in enumerate(defects_to_process):
@@ -741,8 +741,8 @@ def main():
                         help='Specific defect type to generate (e.g., bubble, scratch)')
     parser.add_argument('--output-dir', default='./defect_output', help='Output directory')
     parser.add_argument('--caption', default=None, help='Optional image caption')
-    parser.add_argument('--max-defects', type=int, default=3,
-                        help='Max defects to generate (default: 3)')
+    parser.add_argument('--num-defects', type=int, default=3,
+                        help='Number of defects to generate (default: 3)')
     parser.add_argument('--device', default='cuda', help='Device (cuda/cpu)')
     parser.add_argument('--vlm-model', default='gemma3:12b', help='Local VLM model')
     parser.add_argument('--image-size', type=int, default=512,
@@ -766,7 +766,7 @@ def main():
         product_description=args.product_desc,
         image_path=args.image,
         caption=args.caption,
-        max_defects=args.max_defects,
+        num_defects=args.num_defects,
         defect_type=args.defect_type
     )
 

ArtiAgent - DefectDiffu/src/pipeline/gsam_detector.py

@@ -110,7 +110,7 @@ class GSAMDetector:
             device: Device to use (cuda/cpu)
             openai_client: OpenAI client for vocabulary generation
         """
-        self.gsam_path = os.getcwd()
+        self.gsam_path = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
         
         # Set default paths if not provided
         if grounding_config_file is None:

ArtiAgent - DefectDiffu/src/pipeline/prompts.py

@@ -134,12 +134,13 @@ def plan_defects_for_product(
     image,
     money_manager=None,
     target_defect_type: Optional[str] = None,
-    max_defects: int = 3
+    num_defects: int = 3
 ):
     """
     Agent reasons about possible defects and outputs DefectDiffu-native plans.
     Each plan includes the three text prompts (c_p, c_d, c_f) and w_d/w_p scales.
     """
+
     if client is None:
         client = default_client
     base64_image = encode_image_to_base64(image)
@@ -159,7 +160,7 @@ You are given:
 2. A clean reference image of the product
 {defect_instruction}
 
-Your task is to analyze the product and propose 1-{max_defects} realistic manufacturing or handling defects.
+Your task is to analyze the product and propose {num_defects} realistic manufacturing or handling defects.
 
 For EACH defect, you must produce THREE text prompts for the DefectDiffu diffusion model:
   - c_p (background prompt):  "A photo of <product name>"

ArtiAgent - DefectFill/src/pipeline/gsam_detector.py

@@ -176,7 +176,7 @@ class GSAMDetector:
         entity_predictions = []
     
         # Use VLM to get bboxes for each entity
-        from prompts import get_entity_bboxes
+        from pipeline.prompts import get_entity_bboxes
     
         all_bboxes = {}  # entity -> list of bboxes
     

app.py

@@ -25,6 +25,7 @@ import numpy as np
 import uuid
 import io
 import re
+import importlib.util
 
 
 # =============================================================================
@@ -78,36 +79,124 @@ if not DEFECTDIFFU_CONFIG_PATH.exists():
         json.dump({"ckpt_path": "", "vae_path": "", "vlm_model": "gemma3:12b"}, f, indent=2)
 
 # Setup sys.path for imports
-sys.path.insert(0, str(DEFECTFILL_ROOT / 'src' / 'segment_anything'))
-sys.path.insert(0, str(DEFECTFILL_ROOT / 'src'))
-sys.path.insert(0, str(DEFECTFILL_ROOT / 'pipeline'))
-sys.path.insert(0, str(DEFECTFILL_ROOT))
-sys.path.insert(0, str(DEFECTDIFFU_ROOT))
-sys.path.insert(0, str(DEFECTDIFFU_ROOT / 'pipeline'))
-
-# DefectFill imports
-try:
-    from artiagent_orchestrator import ArtiAgentOrchestrator as DefectFillOrchestrator
-    from align_image_to_reference import align_image_to_reference
-    from detect_similar_product import check_product_training_status
-except Exception as e:
-    print(f"[WARNING] DefectFill imports failed: {e}")
-    DefectFillOrchestrator = None
-    align_image_to_reference = None
-    check_product_training_status = None
-
-# DefectDiffu imports
-try:
-    from artiagent_orchestrator import ArtiAgentOrchestrator as DefectDiffuOrchestrator
-except Exception as e:
-    print(f"[WARNING] DefectDiffu imports failed: {e}")
-    DefectDiffuOrchestrator = None
+# sys.path.insert(0, str(DEFECTFILL_ROOT / 'src' / 'segment_anything'))
+# sys.path.insert(0, str(DEFECTFILL_ROOT / 'src'))
+# sys.path.insert(0, str(DEFECTFILL_ROOT / 'pipeline'))
+# sys.path.insert(0, str(DEFECTFILL_ROOT))
+# sys.path.insert(0, str(DEFECTDIFFU_ROOT))
+# sys.path.insert(0, str(DEFECTDIFFU_ROOT / 'src'))
+# sys.path.insert(0, str(DEFECTDIFFU_ROOT / 'pipeline'))
+
+# =============================================================================
+# Dynamic Import Helpers (avoid module name collisions)
+# =============================================================================
+
+def load_orchestrator_from_path(module_path, class_name="ArtiAgentOrchestrator", extra_paths=None):
+    """
+    Dynamically import a class from a Python file, temporarily adding
+    extra_paths to sys.path so that the module's internal imports
+    resolve to the correct project.
+    """
+    if not module_path.exists():
+        print(f"[ERROR] Module file not found: {module_path}")
+        return None
+
+    original_sys_path = sys.path[:]   # save current state
+
+    try:
+        # Insert project‑specific paths at the front
+        if extra_paths:
+            for p in reversed(extra_paths):   # reverse to keep the given order
+                p_str = str(p)
+                if p_str not in sys.path:
+                    sys.path.insert(0, p_str)
+
+        # Also ensure the module's own directory is available
+        module_dir = module_path.parent
+        if module_dir not in sys.path:
+            sys.path.insert(0, str(module_dir))
+
+        # Use a unique module name to avoid caching collisions
+        module_id = f"_dynamic_{class_name}_{uuid.uuid4().hex[:8]}"
+        spec = importlib.util.spec_from_file_location(module_id, str(module_path))
+        module = importlib.util.module_from_spec(spec)
+        spec.loader.exec_module(module)
+
+        cls = getattr(module, class_name, None)
+        if cls is None:
+            print(f"[ERROR] Class '{class_name}' not found in {module_path}")
+        return cls
+
+    except Exception as e:
+        print(f"[ERROR] Failed to load {module_path}: {e}")
+        traceback.print_exc()
+        return None
+
+    finally:
+        # Restore original sys.path to avoid leaking
+        sys.path[:] = original_sys_path
+
+
+# DefectFill imports — load directly from file to avoid sys.path collision with DefectFill
+extra_paths_df = [
+    DEFECTFILL_ROOT / 'src' / 'segment_anything',
+    DEFECTFILL_ROOT / 'src',
+    DEFECTFILL_ROOT / 'pipeline',
+    DEFECTFILL_ROOT,
+]
+
+df_orchestrator_path = DEFECTFILL_ROOT / "src" / "artiagent_orchestrator.py"
+DefectFillOrchestrator = load_orchestrator_from_path(
+    df_orchestrator_path,
+    "ArtiAgentOrchestrator",
+    extra_paths_df
+)
+print("[INFO] DefectFill orchestrator is ready.", flush=True)
+
+
+# DefectDiffu imports — load directly from file to avoid name collision with DefectDiffu
+extra_paths_dd = [
+    DEFECTDIFFU_ROOT / 'src',
+    DEFECTDIFFU_ROOT / "engine" / "DefectDiffu",
+    DEFECTDIFFU_ROOT,
+]
+
+dd_orchestrator_path = DEFECTDIFFU_ROOT / 'src' / "artiagent_orchestrator.py"
+DefectDiffuOrchestrator = load_orchestrator_from_path(
+    dd_orchestrator_path,
+    "ArtiAgentOrchestrator",
+    extra_paths_dd
+)
+print("[INFO] DefectDiffu orchestrator is ready.")
+
+def load_helper_from_path(module_path, function_name):
+    # Use a generic loader (can reuse load_orchestrator_from_path with no class)
+    # But for functions, you can load the module and extract the function.
+    original_sys_path = sys.path[:]
+    try:
+        # Add DefectFill paths (or pass as extra_paths)
+        sys.path.insert(0, str(DEFECTFILL_ROOT / 'src'))
+        sys.path.insert(0, str(DEFECTFILL_ROOT))
+        spec = importlib.util.spec_from_file_location(f"_helper_{uuid.uuid4().hex[:8]}", str(module_path))
+        module = importlib.util.module_from_spec(spec)
+        spec.loader.exec_module(module)
+        return getattr(module, function_name, None)
+    finally:
+        sys.path[:] = original_sys_path
+
+# Usage:
+align_image_to_reference = load_helper_from_path(
+    DEFECTFILL_ROOT / 'src' / 'align_image_to_reference.py', 'align_image_to_reference'
+)
+check_product_training_status = load_helper_from_path(
+    DEFECTFILL_ROOT / 'src' / 'detect_similar_product.py', 'check_product_training_status'
+)
 
 from flask import Flask, render_template, request, jsonify, send_from_directory
 from flask_cors import CORS
 
 app = Flask(__name__, template_folder=str(BASE_DIR / "templates"), static_folder=str(BASE_DIR / "static"))
-app.config["MAX_CONTENT_LENGTH"] = 32 * 1024 * 1024  # 32MB upload limit
+app.config["MAX_CONTENT_LENGTH"] = 100 * 1024 * 1024  # 100MB upload limit
 CORS(app)
 
 # =============================================================================
@@ -263,7 +352,7 @@ def run_generation_job(job_id, params, mode='defectfill'):
                 result = orchestrator.run(
                     product_description=params['product_desc'],
                     image_path=clean_path,
-                    max_defects=params['num_defects'],
+                    num_defects=params['num_defects'],
                     defect_type=params['defect_type']
                 )
 

config/defectdiffu_config.json

@@ -1,5 +1,5 @@
 {
-  "ckpt_path": "C:\\Users\\admin_mtds\\OneDrive\\Desktop\\ChinKuan\\ArtiAgent - Defect\\engine\\DefectDiffu\\checkpoint_old-4\\model_300.pth",
-  "vae_path": "C:\\Users\\admin_mtds\\OneDrive\\Desktop\\ChinKuan\\ArtiAgent - Defect\\engine\\DefectDiffu\\checkpoints\\sd-vae-ft-mse",
+  "ckpt_path": "C:\\Users\\admin_mtds\\OneDrive\\Desktop\\ChinKuan\\ArtiAgent - latest WebUI\\ArtiAgent - DefectDiffu\\engine\\DefectDiffu\\checkpoint_old-4\\model_300.pth",
+  "vae_path": "C:\\Users\\admin_mtds\\OneDrive\\Desktop\\ChinKuan\\ArtiAgent - latest WebUI\\ArtiAgent - DefectDiffu\\engine\\DefectDiffu\\checkpoints\\sd-vae-ft-mse",
   "vlm_model": "gemma3:12b"
 }