Add image examples to From Image tabs

- Add demo_renders/ (LFS-tracked) with 96 pre-rendered example images
for all CV and TPD mechanisms
- Add example dropdown + gallery preview to CV and TPD "From Image" tabs
- Users can select a mechanism, preview expected outputs, and load
physical images as input with pre-filled scan rates / heating rates

Made-with: Cursor

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+demo_renders/*.png filter=lfs diff=lfs merge=lfs -text

app.py

@@ -36,6 +36,7 @@ from plotting import (
 # ---------------------------------------------------------------------------
 REPO_ROOT = Path(__file__).resolve().parent
 DEMO_DIR = REPO_ROOT / "demo_data"
+DEMO_RENDERS = REPO_ROOT / "demo_renders"
 
 EC_CHECKPOINT = REPO_ROOT / "checkpoints" / "ec_best.pt"
 TPD_CHECKPOINT = REPO_ROOT / "checkpoints" / "tpd_best.pt"
@@ -86,6 +87,75 @@ def _discover_examples():
 CV_EXAMPLES, TPD_EXAMPLES = _discover_examples()
 
 
+def _discover_image_examples():
+    """Build image example catalogs from demo_renders/ directory."""
+    import re
+    cv_img_examples = {}
+    tpd_img_examples = {}
+    cv_output_renders = {}
+    tpd_output_renders = {}
+
+    if not DEMO_RENDERS.is_dir():
+        return cv_img_examples, tpd_img_examples, cv_output_renders, tpd_output_renders
+
+    for p in sorted(DEMO_RENDERS.glob("ec_*_physical.png")):
+        m = re.match(r"ec_(\w+?)_(\d+)mVs_physical\.png", p.name)
+        if not m:
+            continue
+        mech, rate_mVs = m.group(1), int(m.group(2))
+        rate_Vs = rate_mVs / 1000.0
+        cv_img_examples.setdefault(mech, []).append((str(p), rate_Vs))
+
+    for p in sorted(DEMO_RENDERS.glob("tpd_*_physical.png")):
+        m = re.match(r"tpd_(\w+?)_(\d+)_physical\.png", p.name)
+        if not m:
+            continue
+        mech, idx = m.group(1), m.group(2)
+        tpd_img_examples.setdefault(mech, []).append((str(p), idx))
+
+    for mech in cv_img_examples:
+        renders = {}
+        for suffix in ["classification", "posteriors", "reconstruction", "concentration"]:
+            rp = DEMO_RENDERS / f"ec_{mech}_{suffix}.png"
+            if rp.exists():
+                renders[suffix] = str(rp)
+        if renders:
+            cv_output_renders[mech] = renders
+
+    for mech in tpd_img_examples:
+        renders = {}
+        for suffix in ["classification", "posteriors", "reconstruction"]:
+            rp = DEMO_RENDERS / f"tpd_{mech}_{suffix}.png"
+            if rp.exists():
+                renders[suffix] = str(rp)
+        if renders:
+            tpd_output_renders[mech] = renders
+
+    return cv_img_examples, tpd_img_examples, cv_output_renders, tpd_output_renders
+
+
+(CV_IMG_EXAMPLES, TPD_IMG_EXAMPLES,
+ CV_OUTPUT_RENDERS, TPD_OUTPUT_RENDERS) = _discover_image_examples()
+
+
+def _load_cv_image_example(mech_name):
+    """Return (files, scan_rates_str) for a CV image example."""
+    if not mech_name or mech_name not in CV_IMG_EXAMPLES:
+        return [gr.update()] * 2
+    entries = CV_IMG_EXAMPLES[mech_name]
+    files = [e[0] for e in entries]
+    rates_str = ", ".join(f"{e[1]}" for e in entries)
+    return files, rates_str
+
+
+def _load_tpd_image_example(mech_name):
+    """Return (image_path, heating_rate_str) for a TPD image example."""
+    if not mech_name or mech_name not in TPD_IMG_EXAMPLES:
+        return [gr.update()] * 2
+    entries = TPD_IMG_EXAMPLES[mech_name]
+    return entries[0][0], entries[0][1]
+
+
 def _load_cv_example(example_name):
     """Return (files, scan_rates, E0, T, A, C, D, n) for the chosen CV example."""
     if not example_name or example_name not in CV_EXAMPLES:
@@ -790,6 +860,24 @@ def build_app():
                             "Axis bounds are **auto-detected** via OCR — "
                             "override in Advanced if needed."
                         )
+                        if CV_IMG_EXAMPLES:
+                            with gr.Accordion("Try an example (click to load)", open=True):
+                                with gr.Row():
+                                    cv_img_example_dd = gr.Dropdown(
+                                        label="Select mechanism",
+                                        choices=list(CV_IMG_EXAMPLES.keys()),
+                                        value=None,
+                                        interactive=True,
+                                        scale=3,
+                                    )
+                                    cv_img_example_btn = gr.Button(
+                                        "Load Example", variant="secondary", scale=1,
+                                    )
+                                cv_img_example_gallery = gr.Gallery(
+                                    label="Example output (classification → posteriors → reconstruction)",
+                                    columns=3, height=220, object_fit="contain",
+                                    interactive=False,
+                                )
                         cv_img_files = gr.File(
                             label="Plot images (one per scan rate)",
                             file_count="multiple",
@@ -860,6 +948,31 @@ def build_app():
                             inputs=[cv_img_mech_dd, cv_img_state],
                             outputs=[cv_img_posteriors, cv_img_param_table, cv_img_recon, cv_img_conc],
                         )
+                        if CV_IMG_EXAMPLES:
+                            def _on_cv_img_example_select(mech_name):
+                                files, rates = _load_cv_image_example(mech_name)
+                                renders = CV_OUTPUT_RENDERS.get(mech_name, {})
+                                gallery_imgs = [
+                                    renders[k] for k in
+                                    ["classification", "posteriors", "reconstruction"]
+                                    if k in renders
+                                ]
+                                return files, rates, gallery_imgs
+
+                            cv_img_example_btn.click(
+                                _on_cv_img_example_select,
+                                inputs=[cv_img_example_dd],
+                                outputs=[cv_img_files, cv_img_scan_rate, cv_img_example_gallery],
+                            )
+                            cv_img_example_dd.change(
+                                lambda m: [
+                                    CV_OUTPUT_RENDERS.get(m, {}).get(k)
+                                    for k in ["classification", "posteriors", "reconstruction"]
+                                    if CV_OUTPUT_RENDERS.get(m, {}).get(k)
+                                ],
+                                inputs=[cv_img_example_dd],
+                                outputs=[cv_img_example_gallery],
+                            )
 
             # =================================================================
             # Tab 2: TPD Analysis
@@ -940,6 +1053,24 @@ def build_app():
                             "Axis bounds are **auto-detected** via OCR — "
                             "override in Advanced if needed."
                         )
+                        if TPD_IMG_EXAMPLES:
+                            with gr.Accordion("Try an example (click to load)", open=True):
+                                with gr.Row():
+                                    tpd_img_example_dd = gr.Dropdown(
+                                        label="Select mechanism",
+                                        choices=list(TPD_IMG_EXAMPLES.keys()),
+                                        value=None,
+                                        interactive=True,
+                                        scale=3,
+                                    )
+                                    tpd_img_example_btn = gr.Button(
+                                        "Load Example", variant="secondary", scale=1,
+                                    )
+                                tpd_img_example_gallery = gr.Gallery(
+                                    label="Example output (classification → posteriors → reconstruction)",
+                                    columns=3, height=220, object_fit="contain",
+                                    interactive=False,
+                                )
                         tpd_img_files = gr.File(
                             label="Plot images (one per heating rate)",
                             file_count="multiple",
@@ -997,6 +1128,31 @@ def build_app():
                             inputs=[tpd_img_mech_dd, tpd_img_state],
                             outputs=[tpd_img_posteriors, tpd_img_param_table, tpd_img_recon],
                         )
+                        if TPD_IMG_EXAMPLES:
+                            def _on_tpd_img_example_select(mech_name):
+                                files, betas = _load_tpd_image_example(mech_name)
+                                renders = TPD_OUTPUT_RENDERS.get(mech_name, {})
+                                gallery_imgs = [
+                                    renders[k] for k in
+                                    ["classification", "posteriors", "reconstruction"]
+                                    if k in renders
+                                ]
+                                return files, betas, gallery_imgs
+
+                            tpd_img_example_btn.click(
+                                _on_tpd_img_example_select,
+                                inputs=[tpd_img_example_dd],
+                                outputs=[tpd_img_files, tpd_img_betas, tpd_img_example_gallery],
+                            )
+                            tpd_img_example_dd.change(
+                                lambda m: [
+                                    TPD_OUTPUT_RENDERS.get(m, {}).get(k)
+                                    for k in ["classification", "posteriors", "reconstruction"]
+                                    if TPD_OUTPUT_RENDERS.get(m, {}).get(k)
+                                ],
+                                inputs=[tpd_img_example_dd],
+                                outputs=[tpd_img_example_gallery],
+                            )
 
             # =================================================================
             # Tab 3: About