Update app.py

app.py

@@ -377,17 +377,27 @@ ASSETS_DIR = "assets"
 
 
 
+
 def load_performance_reports():
-    """Scan assets/ for *_metrics.json files and pair each with its confusion-matrix
-    image plus any other {prefix}_*.png/.jpg analysis images present (e.g. a
-    melanoma threshold curve, a cluster-confusion breakdown). Returns a list of
-    dicts; empty list if nothing's been uploaded yet."""
+    """Scan assets/ for model performance data in two modes:
+    1. Full reports: a *_metrics.json paired with its confusion-matrix image
+       and any other same-prefix analysis images (threshold curves, cluster
+       breakdowns, etc.).
+    2. Image-only reports: any *_confusion_matrix.{png,jpg,jpeg} that doesn't
+       have a matching metrics.json yet -- shown with its charts but no
+       numeric table, so you don't have to wait on exporting metrics.json
+       just to see the images you already generated.
+    Returns a list of dicts; empty list if nothing's been uploaded at all.
+    """
     import json
  
     reports = []
     if not os.path.isdir(ASSETS_DIR):
         return reports
     all_files = sorted(os.listdir(ASSETS_DIR))
+    claimed = set()  # filenames already used by a full (metrics.json-backed) report
+ 
+    # --- Pass 1: full reports (metrics.json + its images) ---
     for fname in all_files:
         if not fname.endswith("_metrics.json"):
             continue
@@ -403,40 +413,73 @@ def load_performance_reports():
             candidate = os.path.join(ASSETS_DIR, f"{prefix}_confusion_matrix{ext}")
             if os.path.isfile(candidate):
                 image_path = candidate
+                claimed.add(f"{prefix}_confusion_matrix{ext}")
                 break
  
-        # Any other images that share this report's prefix (threshold curves,
-        # cluster breakdowns, etc.) -- shown as extra analysis below the main
-        # confusion matrix. Excludes the confusion matrix itself to avoid
-        # showing it twice.
         extra_images = []
         for other in all_files:
             if not other.startswith(prefix + "_") or not other.lower().endswith((".png", ".jpg", ".jpeg")):
                 continue
             if image_path and other == os.path.basename(image_path):
                 continue
-            label = (
-                other[len(prefix) + 1:]
-                .rsplit(".", 1)[0]
-                .replace("_", " ")
-                .strip()
-                .title()
-            )
+            label = other[len(prefix) + 1:].rsplit(".", 1)[0].replace("_", " ").strip().title()
             extra_images.append({"path": os.path.join(ASSETS_DIR, other), "label": label})
+            claimed.add(other)
  
         reports.append({"data": data, "image_path": image_path, "extra_images": extra_images})
-    return reports
  
+    # --- Pass 2: image-only reports -- any confusion-matrix image not already
+    # claimed by a full report above, grouped with its same-prefix siblings ---
+    seen_prefixes = set()
+    for fname in all_files:
+        if fname in claimed or not fname.lower().endswith((".png", ".jpg", ".jpeg")):
+            continue
+        marker = "_confusion_matrix"
+        idx = fname.lower().find(marker)
+        if idx == -1:
+            continue  # only auto-surface files that look like a confusion matrix
+        prefix = fname[:idx]
+        if prefix in seen_prefixes:
+            continue
+        seen_prefixes.add(prefix)
+ 
+        extra_images = []
+        for other in all_files:
+            if other == fname or other in claimed or not other.startswith(prefix + "_"):
+                continue
+            if not other.lower().endswith((".png", ".jpg", ".jpeg")):
+                continue
+            label = other[len(prefix) + 1:].rsplit(".", 1)[0].replace("_", " ").strip().title()
+            extra_images.append({"path": os.path.join(ASSETS_DIR, other), "label": label})
+            claimed.add(other)
+ 
+        model_name = prefix.replace("_", " ").strip().title() or "Model"
+        reports.append({
+            "data": {"model_name": model_name, "image_only": True},
+            "image_path": os.path.join(ASSETS_DIR, fname),
+            "extra_images": extra_images,
+        })
+ 
+    return reports
+
 
 
 def format_performance_markdown(report):
     data = report["data"]
     lines = [f"### {data.get('model_name', 'Model')}"]
+ 
+    if data.get("image_only"):
+        lines.append(
+            "_Charts available — metrics summary not uploaded yet. Add a matching "
+            "`*_metrics.json` to this prefix for the full accuracy/F1/per-class table._"
+        )
+        return "\n".join(lines)
+ 
     acc = data.get("accuracy")
     f1m = data.get("f1_macro")
     if acc is not None:
         lines.append(f"**Accuracy:** {acc*100:.1f}%  ·  **Macro F1:** {f1m*100:.1f}%" if f1m is not None else f"**Accuracy:** {acc*100:.1f}%")
-
+ 
     per_class = data.get("per_class", {})
     if per_class:
         lines.append("\n| Class | Precision | Recall | F1 | Support |")
@@ -446,14 +489,13 @@ def format_performance_markdown(report):
                 f"| {cls} | {m.get('precision', 0)*100:.1f}% | {m.get('recall', 0)*100:.1f}% "
                 f"| {m.get('f1', 0)*100:.1f}% | {int(m.get('support', 0))} |"
             )
-
+ 
     notes = data.get("notes")
     if notes:
         lines.append(f"\n_Note: {notes}_")
-
+ 
     return "\n".join(lines)
 
-
 ABOUT_MARKDOWN = f"""
 ## About this project
 
@@ -567,6 +609,8 @@ with gr.Blocks(title="Skin Disease Detection — Demo") as demo:
                 gr.Markdown(format_performance_markdown(report))
                 if report["image_path"]:
                     gr.Image(value=report["image_path"], label="Confusion matrix (test set)", show_label=True)
+                for extra in report.get("extra_images", []):
+                    gr.Image(value=extra["path"], label=extra["label"], show_label=True)
 
     with gr.Tab("ℹ️ About"):
         gr.Markdown(ABOUT_MARKDOWN)