Refactor evaluation feedback structure

Author: ShengkaiXu

.idea/.gitignore

@@ -1,6 +1,3 @@
-# -*- coding: utf-8 -*-
-# evaluation_function/evaluation.py
-
 from __future__ import annotations
 
 import os
@@ -25,9 +22,7 @@ class ImageUploadError(Exception):  # type: ignore
 from .yolo_pipeline import run_yolo_pipeline
 
 
-# ----------------------------
 # URL / path helpers
-# ----------------------------
 def file_url_to_local_path(url: str) -> str:
     """
     Convert file:// URL to local path.
@@ -95,133 +90,145 @@ def _pget(params: Params, key: str, default: Any) -> Any:
         except Exception:
             return default
 
+def _items_to_feedback_html(items):
+    lines = []
+    for k, v in items:
+        k = str(k).strip() if k is not None else ""
+        v = str(v).strip() if v is not None else ""
+        if k:
+            lines.append(f"{k}: {v}")
+        else:
+            lines.append(v)
+    return "<br>".join(lines)
+
 
-# ----------------------------
 # Main entry
-# ----------------------------
 def evaluation_function(response: Any, answer: Any, params: Params) -> Result:
-    """
-    Lambda Feedback evaluation entry.
-
-    Expected response format for an image response area:
-        response = [{"url": "https://..."}, {"url": "https://..."}]
-    Local dev also allows:
-        "url": "file:///C:/path/to/image.jpg"
-
-    This function will:
-      - load each image by URL
-      - run YOLO pipeline
-      - return feedback + (optional) annotated images via upload_image()
-    """
+    try:
+        # Validate input
+        if not isinstance(response, list) or len(response) == 0:
+            items = [("Response", "Please upload at least one image.")]
+            feedback_html = _items_to_feedback_html(items)
+            try:
+                return Result(is_correct=False, feedback=feedback_html, feedback_items=items)
+            except TypeError:
+                return Result(is_correct=False, feedback_items=items)
+
+        # Optional controls (safe defaults)
+        # Default: NO image upload (text only), to match your current goal
+        return_images: bool = bool(_pget(params, "return_images", False))
+        debug: bool = bool(_pget(params, "debug", False))
+
+        # Relative model filenames stored in evaluation_function/
+        gear_model_rel = str(_pget(params, "gear_model_rel", "gear_model.pt"))
+        shaft_model_rel = str(_pget(params, "shaft_model_rel", "shaft_model.pt"))
+
+
+        # Process images
+        merged_errors: List[Dict[str, str]] = []
+        merged_summaries: List[Dict[str, Any]] = []
+        merged_ratios: List[Dict[str, Any]] = []
+
+        feedback_items: List[Tuple[str, str]] = []
+
+        for idx, item in enumerate(response):
+            url = item.get("url") if isinstance(item, dict) else None
+            if not url:
+                merged_errors.append({
+                    "code": "NO_URL",
+                    "message": f"Image [{idx}] has no 'url' field."
+                })
+                continue
+
+            img_bgr, err = _load_bgr_image_from_url(url)
+            if img_bgr is None:
+                merged_errors.append({
+                    "code": "LOAD_FAIL",
+                    "message": f"Failed to load image [{idx}] from URL. ({err})"
+                })
+                if debug:
+                    feedback_items.append((f"Input URL [{idx}]", str(url)))
+                continue
+
+            # Run pipeline (your external YOLO pipeline)
+            out = run_yolo_pipeline(
+                img_bgr=img_bgr,
+                gear_model_rel=gear_model_rel,
+                shaft_model_rel=shaft_model_rel,
+                return_images=return_images,
+            )
+
+            # Collect outputs safely
+            summary = out.get("summary", {})
+            ratio = out.get("ratio", {})
+            errors = out.get("errors", [])
+
+            if isinstance(summary, dict):
+                merged_summaries.append(summary)
+            if isinstance(ratio, dict):
+                merged_ratios.append(ratio)
+            if isinstance(errors, list):
+                merged_errors.extend(errors)
+
+            # Optional annotated images upload (disabled by default)
+            if return_images:
+                imgs = out.get("images", None)
+                if isinstance(imgs, dict) and upload_image is not None:
+                    for key in ("det_img", "label_img"):
+                        if key in imgs and isinstance(imgs[key], np.ndarray):
+                            try:
+                                png_bytes = _cv2_bgr_to_png_bytes(imgs[key])
+                                img_url = upload_image(png_bytes, "eduvision")
+                                feedback_items.append(
+                                    (f"{key} [{idx}]", f"<a href=\"{img_url}\" target=\"_blank\">{key}</a>")
+                                )
+                            except ImageUploadError as e:
+                                merged_errors.append({
+                                    "code": "UPLOAD_FAIL",
+                                    "message": f"Failed to upload {key} for image[{idx}]: {e}"
+                                })
+                            except Exception as e:
+                                merged_errors.append({
+                                    "code": "UPLOAD_FAIL",
+                                    "message": f"Failed to encode/upload {key} for image[{idx}]: {e}"
+                                })
+                elif upload_image is None and debug:
+                    feedback_items.append(("Images", "return_images=True but upload_image() is not available in this lf_toolkit version."))
 
-    # ---------------------------
-    # Validate input
-    # ---------------------------
-    if not isinstance(response, list) or len(response) == 0:
-        return Result(
-            is_correct=False,
-            feedback_items=[("Response", "Please upload at least one image.")]
-        )
-
-    # Optional controls (safe defaults)
-    return_images: bool = bool(_pget(params, "return_images", False))
-    debug: bool = bool(_pget(params, "debug", False))
-
-    # Relative model filenames stored in evaluation_function/
-    gear_model_rel = str(_pget(params, "gear_model_rel", "gear_model.pt"))
-    shaft_model_rel = str(_pget(params, "shaft_model_rel", "shaft_model.pt"))
-
-    # ---------------------------
-    # Process images
-    # ---------------------------
-    merged_errors: List[Dict[str, str]] = []
-    merged_summaries: List[Dict[str, Any]] = []
-    merged_ratios: List[Dict[str, Any]] = []
-
-    feedback_items: List[Tuple[str, str]] = []
-
-    for idx, item in enumerate(response):
-        url = item.get("url") if isinstance(item, dict) else None
-        if not url:
-            merged_errors.append({
-                "code": "NO_URL",
-                "message": f"Image [{idx}] has no 'url' field."
-            })
-            continue
-
-        img_bgr, err = _load_bgr_image_from_url(url)
-        if img_bgr is None:
-            merged_errors.append({
-                "code": "LOAD_FAIL",
-                "message": f"Failed to load image [{idx}] from URL. ({err})"
-            })
             if debug:
                 feedback_items.append((f"Input URL [{idx}]", str(url)))
-            continue
-
-        # Run pipeline
-        out = run_yolo_pipeline(
-            img_bgr=img_bgr,
-            gear_model_rel=gear_model_rel,
-            shaft_model_rel=shaft_model_rel,
-            return_images=return_images,
-        )
-
-        merged_summaries.append(out.get("summary", {}))
-        merged_ratios.append(out.get("ratio", {}))
-        merged_errors.extend(out.get("errors", []))
-
-        # Upload annotated images (optional, only if upload_image exists)
-        if return_images:
-            imgs = out.get("images", None)
-            if isinstance(imgs, dict) and upload_image is not None:
-                for key in ("det_img", "label_img"):
-                    if key in imgs and isinstance(imgs[key], np.ndarray):
-                        try:
-                            png_bytes = _cv2_bgr_to_png_bytes(imgs[key])
-                            img_url = upload_image(png_bytes, "eduvision")  # folder/tag
-                            feedback_items.append(
-                                (f"{key} [{idx}]", f"<a href=\"{img_url}\" target=\"_blank\">{key}</a>")
-                            )
-                        except ImageUploadError as e:
-                            merged_errors.append({
-                                "code": "UPLOAD_FAIL",
-                                "message": f"Failed to upload {key} for image[{idx}]: {e}"
-                            })
-                        except Exception as e:
-                            merged_errors.append({
-                                "code": "UPLOAD_FAIL",
-                                "message": f"Failed to encode/upload {key} for image[{idx}]: {e}"
-                            })
-            elif return_images and upload_image is None:
-                # Don't fail; just inform in debug mode
-                if debug:
-                    feedback_items.append(("Images", "return_images=True but upload_image() not available in this lf_toolkit version."))
 
-        if debug:
-            feedback_items.append((f"Input URL [{idx}]", str(url)))
+        # Decide correctness
+        # Your rule: incorrect if any error code starts with "E_"
+        has_E = any(str(e.get("code", "")).startswith("E_") for e in merged_errors)
+        is_correct = (not has_E)
+
+        # Text feedback
+        if merged_summaries:
+            feedback_items.append(("Summary", str(merged_summaries[-1])))
 
-    # ---------------------------
-    # Decide correctness
-    # ---------------------------
-    # Your rule: incorrect if any error code starts with "E_"
-    has_E = any(str(e.get("code", "")).startswith("E_") for e in merged_errors)
-    is_correct = (not has_E)
+        if merged_ratios:
+            feedback_items.append(("Ratio", str(merged_ratios[-1])))
 
-    # ---------------------------
-    # Text feedback
-    # ---------------------------
-    if merged_summaries:
-        feedback_items.append(("Summary", str(merged_summaries[-1])))
+        if merged_errors:
+            lines = [f"- {e.get('code', 'ERR')}: {e.get('message', '')}" for e in merged_errors]
+            feedback_items.append(("Issues", "\n".join(lines)))
 
-    if merged_ratios:
-        feedback_items.append(("Ratio", str(merged_ratios[-1])))
+        if not feedback_items:
+            feedback_items = [("Result", "No valid images could be processed.")]
 
-    if merged_errors:
-        lines = [f"- {e.get('code', 'ERR')}: {e.get('message', '')}" for e in merged_errors]
-        feedback_items.append(("Issues", "\n".join(lines)))
+        feedback_html = _items_to_feedback_html(feedback_items)
 
-    if not feedback_items:
-        feedback_items = [("Result", "No valid images could be processed.")]
+        try:
+            return Result(is_correct=is_correct, feedback=feedback_html, feedback_items=feedback_items)
+        except TypeError:
+            return Result(is_correct=is_correct, feedback_items=feedback_items)
 
-    return Result(is_correct=is_correct, feedback_items=feedback_items)
+    except Exception as e:
+        # Absolute last-resort: never crash the platform UI
+        items = [("Error", f"{type(e).__name__}: {e}")]
+        feedback_html = _items_to_feedback_html(items)
+        try:
+            return Result(is_correct=False, feedback=feedback_html, feedback_items=items)
+        except TypeError:
+            return Result(is_correct=False, feedback_items=items)