Update app.py

app.py

@@ -1,1503 +1,723 @@
 import os
-
 import json
-
 import hashlib
-
 import random
-
 import threading
-
 import time
-
 from dataclasses import dataclass
-
 from typing import List, Dict, Any
 
-
-
 import gradio as gr
-
 from PIL import Image
-
 from huggingface_hub import HfApi, CommitOperationAdd
 
-
-
 # ----------------------
-
 # Configuration
-
 # ----------------------
-
 # --- HF Repo ---
-
 HF_RESULTS_REPO = os.getenv("HF_RESULTS_REPO")
-
 HF_RESULTS_REPO_TYPE = "dataset"
-
 HF_TOKEN = os.getenv("HF_TOKEN")
-
 _hf_api = HfApi(token=HF_TOKEN)
 
-
-
 # --- Main settings ---
-
-# UPDATED: Set to 20 as requested
-
 TARGET_PER_PERSON = 20
-
 CONTACT_EMAIL = "ffallah@asu.edu"
 
-
-
 # --- Paths ---
-
-# We still use the JSON file to get the list of filenames, 
-
 CAPTIONS_JSON_PATH = os.environ.get("CAPTIONS_JSON_PATH", "data/captions.json")
 
-
-
-# Folders with matching filenames across all FIVE folders:
-
 GT_MASKED_DIR   = "data/gt_b"   # Image 1
-
 GT_UNMASKED_DIR = "data/adc_b"  # Image 2
-
 SR_DIR          = "data/sr_b"   # Image 3
-
 ORIGINAL_DIR    = "data/lr_b"   # Image 4
-
 IMAGE_5_DIR     = "data/see_b"  # Image 5
 
-
-
 # --- Results ---
-
 RESULTS_DIR = "results"
-
 PROGRESS_PATH = os.path.join(RESULTS_DIR, "progress.json")
-
 ALL_RESULTS_JSONL = os.path.join(RESULTS_DIR, "all_results.jsonl")
-
-SAVE_PII = True # Set to False to anonymize saved name/email
-
-
+SAVE_PII = True
 
 WRITE_LOCK = threading.Lock()
-
-STRICT_ENFORCEMENT = False  # UPDATED: Set to False to prevent crashes if dataset size != target
-
-
+STRICT_ENFORCEMENT = False
 
 # ----------------------
-
 # Data model
-
 # ----------------------
-
 @dataclass
-
 class Sample:
-
     sample_id: str
-
     masked_gt_path: str   # Image 1
-
     unmasked_gt_path: str # Image 2
-
     sr_path: str          # Image 3
-
     original_path: str    # Image 4
-
     image_5_path: str     # Image 5
 
-
-
 # ----------------------
-
 # Helpers
-
 # ----------------------
+# def ensure_sample_objects(samples_input):
+#     """
+#     Accepts either:
+#      - list[Sample] (already objects), or
+#      - list[dict] (serialized Sample.__dict__)
+#     Returns list[Sample].
+#     """
+#     if not samples_input:
+#         return []
+#     if isinstance(samples_input, list):
+#         if len(samples_input) == 0:
+#             return []
+#         first = samples_input[0]
+#         if isinstance(first, dict):
+#             try:
+#                 return [Sample(**s) for s in samples_input]
+#             except Exception:
+#                 # fall through to returning empty to avoid crashes
+#                 return []
+#         elif isinstance(first, Sample):
+#             return samples_input
+#     return []
 
 def user_target_count(samples: List[Sample]) -> int:
-
-    # UPDATED: Logic to be more robust. 
-
-    # It takes the minimum of the available samples or the target.
-
-    # This prevents crashes if you have fewer or more images than 20.
-
     return min(len(samples), TARGET_PER_PERSON)
 
-
-
 def user_left_count(user_seen: List[str], samples: List[Sample]) -> int:
-
     target = user_target_count(samples)
-
-    seen = set(user_seen)
-
-    # Only count seen images that are actually in the current sample list
-
-    allowed_ids = {s.sample_id for s in samples} 
-
+    seen = set(user_seen or [])
+    allowed_ids = {s.sample_id for s in samples}
     seen_in_allowed = len([sid for sid in seen if sid in allowed_ids])
-
     return max(0, target - seen_in_allowed)
 
-
-
 def _ensure_private_repo(repo_id: str):
-
     try:
-
         _hf_api.repo_info(repo_id, repo_type=HF_RESULTS_REPO_TYPE)
-
     except Exception:
-
         _hf_api.create_repo(repo_id=repo_id, repo_type=HF_RESULTS_REPO_TYPE, private=True)
 
-
-
 def push_results_to_private_repo(uid: str):
-
     if not HF_TOKEN or not HF_RESULTS_REPO:
-
         return
-
     try:
-
-        # _ensure_private_repo(HF_RESULTS_REPO)
-
         os.makedirs(RESULTS_DIR, exist_ok=True)
-
-        # # Ensure files exist
-
-        # if not os.path.exists(ALL_RESULTS_JSONL):
-
-        #     open(ALL_RESULTS_JSONL, "a").close()
-
-        
-
         user_file = os.path.join(RESULTS_DIR, f"{uid}.jsonl")
 
-        # if not os.path.exists(user_file):
-
-        #     open(user_file, "a").close()
-
-
-
         ops = [
-
             CommitOperationAdd(
-
                 path_in_repo="results/all_results.jsonl",
-
                 path_or_fileobj=ALL_RESULTS_JSONL
-
             ),
-
             CommitOperationAdd(
-
                 path_in_repo=f"results/users/{uid}.jsonl",
-
                 path_or_fileobj=user_file
-
             ),
-
             CommitOperationAdd(
-
                 path_in_repo="results/progress.json",
-
                 path_or_fileobj=PROGRESS_PATH
-
             ),
-
         ]
-
         _hf_api.create_commit(
-
             repo_id=HF_RESULTS_REPO,
-
             repo_type=HF_RESULTS_REPO_TYPE,
-
             operations=ops,
-
             commit_message="Update RTS eval results"
-
         )
-
     except Exception as e:
-
         print("[WARN] push_results_to_private_repo failed:", e)
 
-
-
 def ensure_paths():
-
     os.makedirs(RESULTS_DIR, exist_ok=True)
-
     for pth, name in [
-
         (GT_MASKED_DIR, "GT_MASKED_DIR"),
-
         (GT_UNMASKED_DIR, "GT_UNMASKED_DIR"),
-
         (SR_DIR, "SR_DIR"),
-
         (ORIGINAL_DIR, "ORIGINAL_DIR"),
-
         (IMAGE_5_DIR, "IMAGE_5_DIR"),
-
     ]:
-
         if not os.path.isdir(pth):
-
-            # We just print a warning instead of crashing, to allow partial setup
-
             print(f"Warning: Directory '{pth}' for {name} not found.")
 
-
-
 def load_image(path: str) -> Image.Image:
-
-    if not os.path.exists(path):
-
-        return Image.new("RGB", (256, 256), color="gray") # Return placeholder if missing
-
-    return Image.open(path).convert("RGB")
-
-
+    if not path or not os.path.exists(path):
+        # return a simple placeholder image so UI doesn't crash
+        return Image.new("RGB", (256, 256), color="gray")
+    try:
+        return Image.open(path).convert("RGB")
+    except Exception:
+        return Image.new("RGB", (256, 256), color="gray")
 
 def load_dataset(captions_path: str, gt_masked_dir: str, gt_unmasked_dir: str, sr_dir: str, original_dir: str, image_5_dir: str) -> List[Sample]:
-
     if not os.path.exists(captions_path):
-
+        print(f"Captions file not found at {captions_path}")
         return []
 
-
-
     with open(captions_path, "r", encoding="utf-8") as f:
-
-        captions_data = json.load(f)
-
-
+        try:
+            captions_data = json.load(f)
+        except Exception:
+            print("Failed to parse captions JSON.")
+            return []
 
     samples: List[Sample] = []
-
     for item in captions_data:
-
         base_filename = item.get("image")
-
         if not base_filename:
-
             continue
 
-
-
         sample_id = os.path.splitext(base_filename)[0]
-
-        
-
-        # Define all 5 target paths
-
         paths = {
-
             "masked": os.path.join(gt_masked_dir, base_filename),
-
             "unmasked": os.path.join(gt_unmasked_dir, base_filename),
-
             "sr": os.path.join(sr_dir, base_filename),
-
             "original": os.path.join(original_dir, base_filename),
-
             "img5": os.path.join(image_5_dir, base_filename)
-
         }
 
-
-
-        # STRICT CHECK: All 5 must exist
-
-        if all(os.path.exists(p) for p in paths.values()):
-
-            samples.append(
-
-                Sample(
-
-                    sample_id=sample_id,
-
-                    masked_gt_path=paths["masked"],
-
-                    unmasked_gt_path=paths["unmasked"],
-
-                    sr_path=paths["sr"],
-
-                    original_path=paths["original"],
-
-                    image_5_path=paths["img5"]
-
-                )
-
+        # If strict enforcement required, require all five files to exist.
+        if STRICT_ENFORCEMENT:
+            if not all(os.path.exists(p) for p in paths.values()):
+                missing = [k for k, v in paths.items() if not os.path.exists(v)]
+                print(f"Skipping {base_filename}: Missing in folders {missing}")
+                continue
+
+        # In non-strict mode, it's okay to include samples even if some files missing;
+        # we will supply placeholders at load time.
+        samples.append(
+            Sample(
+                sample_id=sample_id,
+                masked_gt_path=paths["masked"],
+                unmasked_gt_path=paths["unmasked"],
+                sr_path=paths["sr"],
+                original_path=paths["original"],
+                image_5_path=paths["img5"]
             )
-
-        else:
-
-            # Debugging: Find out which folder is the culprit
-
-            missing = [k for k, v in paths.items() if not os.path.exists(v)]
-
-            print(f"Skipping {base_filename}: Missing in folders {missing}")
-
-
+        )
 
     return samples
 
-
-
 # ----------------------
-
 # Progress & results I/O
-
 # ----------------------
-
 def hash_user_id(name: str, email: str) -> str:
-
     norm = (name or "").strip().lower() + "|" + (email or "").strip().lower()
-
     return hashlib.sha256(norm.encode("utf-8")).hexdigest()[:16]
 
-
-
 def load_progress() -> Dict[str, Dict[str, Any]]:
-
     if not os.path.exists(PROGRESS_PATH):
-
         return {}
-
     try:
-
         with open(PROGRESS_PATH, "r", encoding="utf-8") as f:
-
             return json.load(f)
-
     except Exception:
-
         return {}
 
-
-
 def save_progress(progress: Dict[str, Dict[str, Any]]):
-
     with WRITE_LOCK:
-
         with open(PROGRESS_PATH, "w", encoding="utf-8") as f:
-
             json.dump(progress, f, ensure_ascii=False, indent=2)
 
-
-
 def append_jsonl(path: str, record: Dict[str, Any]):
-
     line = json.dumps(record, ensure_ascii=False)
-
     with WRITE_LOCK:
-
         with open(path, "a", encoding="utf-8") as f:
-
             f.write(line + "\n")
 
-
-
 # ----------------------
-
 # LOGIC FOR CONVERTING SLIDERS TO RANK
-
 # ----------------------
-
 def convert_scores_to_rank(s1, s2, s3, s4, s5) -> Dict[str, int]:
-
-    """
-
-    Takes 5 scores (1-10). Returns a dictionary:
-
-    {'image_1': rank, 'image_2': rank...}
-
-    where Rank 1 is the Highest Score.
-
-    """
-
     scores = [
-
         ("image_1", s1),
-
         ("image_2", s2),
-
         ("image_3", s3),
-
         ("image_4", s4),
-
         ("image_5", s5)
-
     ]
-
-    # Sort by score descending (High score first)
-
     scores.sort(key=lambda x: x[1], reverse=True)
-
-    
-
     ranks = {}
-
     current_rank = 1
-
     for img_key, score in scores:
-
         ranks[img_key] = current_rank
-
         current_rank += 1
-
-        
-
     return ranks
 
-
-
 # ----------------------
-
 # App logic
-
 # ----------------------
-
 def pick_next_index(user_seen: List[str], samples: List[Sample]) -> int:
-
-    # Logic: Only pick from samples that match the criteria
-
-    seen_set = set(user_seen)
-
+    # FIX: define seen_set and use samples directly
+    seen_set = set(user_seen or [])
     remaining = [i for i, s in enumerate(samples) if s.sample_id not in seen_set]
-
-    
-
     if not remaining:
-
         return -1
-
     return random.choice(remaining)
 
-
-
 def start_or_resume(name: str, email: str):
-
     if not name or not email:
-
         raise gr.Error("Please enter your name and email to begin.")
 
-
-
     ensure_paths()
-
     samples = load_dataset(CAPTIONS_JSON_PATH, GT_MASKED_DIR, GT_UNMASKED_DIR, SR_DIR, ORIGINAL_DIR, IMAGE_5_DIR)
 
-    
-
     if not samples:
-
-         raise gr.Error("No images found. Please check dataset configuration.")
-
-
+        raise gr.Error("No images found. Please check dataset configuration.")
 
     uid = hash_user_id(name, email)
-
     progress = load_progress()
-
     if uid not in progress:
-
         progress[uid] = {"seen": []}
-
         save_progress(progress)
 
-
-
     user_seen: List[str] = progress[uid].get("seen", [])
-
     left = user_left_count(user_seen, samples)
 
-
+    # placeholder image to avoid Gradio trying to load None
+    placeholder_img = Image.new("RGB", (256, 256), color="gray")
 
     # If the user has finished their target
-
     if left == 0 and len(user_seen) >= user_target_count(samples):
-
         status = (
-
             f"Welcome back, {name}. You’ve completed all {user_target_count(samples)} images. 🎉\n"
-
             f"Your personal results file: {os.path.join(RESULTS_DIR, f'{uid}.jsonl')}"
-
         )
-
         return (
-
-            uid, samples, user_seen, -1,
-
-            None, None, None, None, None, # images
-
+            uid,
+            samples,
+            user_seen,
+            -1,
+            placeholder_img, placeholder_img, placeholder_img, placeholder_img, placeholder_img,
             status,
-
             os.path.join(RESULTS_DIR, f"{uid}.jsonl"),
-
             gr.update(visible=False),
-
             gr.update(visible=True),
-
             gr.update(visible=True),
-
         )
 
-
-
     idx = pick_next_index(user_seen, samples)
-
-    if idx == -1: 
-
-        # Case where target not reached but no fresh images left
-
-        return (uid, samples, user_seen, -1, None, None, None, None, None, "No more new images available.", "", gr.update(visible=False), gr.update(visible=True), gr.update(visible=True))
-
-
+    if idx == -1:
+        return (
+            uid,
+            samples,
+            user_seen,
+            -1,
+            placeholder_img, placeholder_img, placeholder_img, placeholder_img, placeholder_img,
+            "No more new images available.",
+            "",
+            gr.update(visible=False),
+            gr.update(visible=True),
+            gr.update(visible=True)
+        )
 
     sample = samples[idx]
 
-
-
     status = (
-
         f"Welcome, {name}. Personal progress — images left: {left} of {user_target_count(samples)}.\n"
-
         f"Current sample: {sample.sample_id}"
-
     )
 
-
-
     os.makedirs(RESULTS_DIR, exist_ok=True)
-
     user_file_path = os.path.join(RESULTS_DIR, f"{uid}.jsonl")
 
-
-
     return (
-
-        uid, samples, user_seen, idx,
-
+        uid,
+        samples,
+        user_seen,
+        idx,
         load_image(sample.masked_gt_path),
-
         load_image(sample.unmasked_gt_path),
-
         load_image(sample.sr_path),
-
         load_image(sample.original_path),
-
         load_image(sample.image_5_path),
-
         status,
-
         user_file_path,
-
         gr.update(visible=True),
-
         gr.update(visible=False),
-
         gr.update(visible=False),
-
     )
 
 
-
 def _save_record_and_progress(
-
     name: str,
-
     email: str,
-
     uid: str,
-
     samples: List[Sample],
-
     user_seen: List[str],
-
     idx: int,
-
     score_1: float,
-
     score_2: float,
-
     score_3: float,
-
     score_4: float,
-
     score_5: float,
-
     q1_notes: str,
-
 ):
-
     if not name or not email:
-
         raise gr.Error("Please enter your name and email.")
 
-
-
+    # FIX: use samples directly
     if idx is None or idx < 0 or idx >= len(samples):
-
         return load_progress()
 
-
-
-    # --- CALCULATE RANK FROM SLIDERS ---
-
     rank_dict = convert_scores_to_rank(score_1, score_2, score_3, score_4, score_5)
 
-
-
     sample = samples[idx]
-
     progress = load_progress()
-
     progress.setdefault(uid, {"seen": []})
-
     seen = set(progress[uid].get("seen", []))
 
-
-
     if sample.sample_id in seen:
-
         return progress
 
-    
-
-    # We allow saving even if target met, just in case, but usually UI stops them.
-
-
-
     record: Dict[str, Any] = {
-
         "timestamp": time.strftime("%Y-%m-%dT%H:%M:%SZ", time.gmtime()),
-
         "user_id": uid,
-
         "name": name if SAVE_PII else None,
-
         "email": email if SAVE_PII else None,
-
         "sample_id": sample.sample_id,
-
-        # "image_paths": {
-
-        #     "masked_gt": sample.masked_gt_path,
-
-        #     "unmasked_gt": sample.unmasked_gt_path,
-
-        #     "sr": sample.sr_path,
-
-        #     "original": sample.original_path,
-
-        #     "image_5": sample.image_5_path,
-
-        # },
-
-        # Save raw scores (1-10) and the ranking
-
         "raw_scores": {
-
             "image_1": score_1,
-
             "image_2": score_2,
-
             "image_3": score_3,
-
             "image_4": score_4,
-
             "image_5": score_5,
-
         },
-
         "responses": {
-
-            # "image_ranking": rank_dict, # Format: {"image_1": 1, "image_2": 4, ...}
-
             "notes": q1_notes or "",
-
+            "image_ranking": rank_dict,
         },
-
     }
 
-
-
     os.makedirs(RESULTS_DIR, exist_ok=True)
-
     append_jsonl(os.path.join(RESULTS_DIR, f"{uid}.jsonl"), record)
-
     append_jsonl(ALL_RESULTS_JSONL, record)
 
-    # push_results_to_private_repo(uid) 
-
-    thread = threading.Thread(target=push_results_to_private_repo, args=(uid,))
-
-    thread.start()
-
-
+    # start background push but don't let failures crash the app
+    try:
+        thread = threading.Thread(target=push_results_to_private_repo, args=(uid,))
+        thread.daemon = True
+        thread.start()
+    except Exception:
+        pass
 
     seen.add(sample.sample_id)
-
     progress[uid]["seen"] = sorted(list(seen))
-
     save_progress(progress)
-
     return progress
 
-
-
 # ----------------------
-
 # Buttons
-
 # ----------------------
-
 def submit_finish(
-
     name: str,
-
     email: str,
-
     uid: str,
-
     samples: List[Sample],
-
     user_seen: List[str],
-
     idx: int,
-
     s1: float, s2: float, s3: float, s4: float, s5: float,
-
     q1_notes: str
-
 ):
-
     try:
-
         _save_record_and_progress(
-
             name, email, uid, samples, user_seen, idx,
-
             s1, s2, s3, s4, s5,
-
             q1_notes
-
         )
-
     except gr.Error:
-
         return (
-
             user_seen, idx,
-
             gr.update(), gr.update(), gr.update(), gr.update(), gr.update(),
-
-            gr.update(), 
-
+            gr.update(),
             gr.update(), gr.update(), gr.update(), gr.update(), gr.update(),
-
             gr.update(),
-
         )
 
-
-
     return (
-
         user_seen, idx,
-
         gr.update(value=None), gr.update(value=None), gr.update(value=None), gr.update(value=None), gr.update(value=None),
-
-        gr.update(value=""), 
-
+        gr.update(value=""),
         gr.update(value="Finished!"),
-
         gr.update(value=5), gr.update(value=5), gr.update(value=5), gr.update(value=5), gr.update(value=5),
-
-        gr.update(value=None), 
-
+        gr.update(value=None),
     )
 
-    
-
 def pause_exit(user_seen, samples):
-
     return user_seen, samples
 
-    
-
 def submit_next_image(
-
     name: str,
-
     email: str,
-
     uid: str,
-
     samples: List[Sample],
-
-    user_seen: List[str],
-
+    user_seen: List[Sample],
     idx: int,
-
     s1: float, s2: float, s3: float, s4: float, s5: float,
-
     q1_notes: str
-
 ):
-
     try:
-
         progress = _save_record_and_progress(
-
             name, email, uid, samples, user_seen, idx,
-
             s1, s2, s3, s4, s5,
-
             q1_notes
-
         )
+    except gr.Error as e:
+        raise e
 
-    except gr.Error as e:
-
-        raise e
-
-        # return (
-
-        #     user_seen, idx,
-
-        #     gr.update(), gr.update(), gr.update(), gr.update(), gr.update(),
-
-        #     gr.update(), 
-
-        #     gr.update(), gr.update(), gr.update(), gr.update(), gr.update(),
-
-        #     gr.update(),
-
-        # )
-
-    
-
-    # left_after = user_left_count(progress[uid]["seen"], samples)
-
-    # target = user_target_count(samples)
-
-    updated_seen = progress[uid]["seen"]
-
-
-
-    if len(updated_seen) >= TARGET_PER_PERSON:
-
-        status = (
-
-            f"Saved! You’ve completed all {target} images. 🎉 "
-
-            f"Click **Exit** to close this session."
-
-        )
-
-        return (
-
-            updated_seen, -1, 
-
-            None, None, None, None, None, # No more images to load
-
-            gr.update(value="Target reached!"), # Status
-
-            gr.update(value=""), # Clear notes
-
-            5, 5, 5, 5, 5 # Reset sliders
-
-        )
-
-    
-
-    # if left_after == 0:
-
-    #     status = (
-
-    #         f"Saved! You’ve completed all {target} images. 🎉 "
-
-    #         f"Click **Exit** to close this session."
-
-    #     )
-
-    #     return (
-
-    #                 updated_seen, -1,
-
-    #                 None, None, None, None, None,  # Return None to avoid image load errors
-
-    #                 gr.update(value="Target reached! Processing..."), 
-
-    #                 gr.update(value=""),
-
-    #                 5, 5, 5, 5, 5, 
-
-    #                 gr.update(value=None)
-
-    #             )
-
-
-
-    idx_next = pick_next_index(updated_seen, samples)
-
-    if idx_next == -1:
-
-        return (updated_seen, -1, None, None, None, None, None, "No more images.", "", 5, 5, 5, 5, 5)
-
-         # Fallback if no images left
-
-         # return (
-
-         #    progress[uid]["seen"], -1,
-
-         #    None, None, None, None, None,
-
-         #    gr.update(value="No more images."),
-
-         #    gr.update(value=""),
-
-         #    gr.update(value=5), gr.update(value=5), gr.update(value=5), gr.update(value=5), gr.update(value=5),
-
-         #    gr.update(value=None),
-
-         # )
-
-
-
-    sample_next = samples[idx_next]
-
-
-
-    status =""
+    seen_list = progress.get(uid, {}).get("seen", [])
+    left_after = user_left_count(seen_list, samples)
+    target = user_target_count(samples)
 
-    # (
+    # placeholder image to avoid Gradio trying to load None
+    placeholder_img = Image.new("RGB", (256, 256), color="gray")
 
-    #     f"Saved! Personal progress — images left: {left_after} of {target}.\n"
+    # If user reached the target, return placeholders for images and let the then() chain show thanks
+    if left_after == 0:
+        status = (
+            f"Saved! You’ve completed all {target} images. 🎉 "
+            f"Click **Exit** to close this session."
+        )
+        return (
+            seen_list, -1,
+            placeholder_img, placeholder_img, placeholder_img, placeholder_img, placeholder_img,
+            gr.update(value=status),
+            gr.update(value=""),
+            5, 5, 5, 5, 5,
+        )
 
-    #     f"Next sample: {sample_next.sample_id}"
+    idx_next = pick_next_index(seen_list, samples)
+    if idx_next == -1:
+        # no more images but target not met (rare). return placeholders too.
+        return (
+            seen_list, -1,
+            placeholder_img, placeholder_img, placeholder_img, placeholder_img, placeholder_img,
+            "No more images.",
+            "",
+            5, 5, 5, 5, 5,
+        )
 
-    # )
+    # FIX: define sample_next correctly
+    sample_next = samples[idx_next]
 
     return (
-
-        updated_seen, idx_next,
-
+        seen_list, idx_next,
         load_image(sample_next.masked_gt_path),
-
         load_image(sample_next.unmasked_gt_path),
-
         load_image(sample_next.sr_path),
-
         load_image(sample_next.original_path),
-
         load_image(sample_next.image_5_path),
-
         gr.update(value=""),
-
         gr.update(value=""),
-
         5, 5, 5, 5, 5,
-
-        
-
     )
 
-    # return (
-
-    #     progress[uid]["seen"], idx_next,
-
-    #     load_image(sample_next.masked_gt_path),
-
-    #     load_image(sample_next.unmasked_gt_path),
-
-    #     load_image(sample_next.sr_path),
-
-    #     load_image(sample_next.original_path),
-
-    #     load_image(sample_next.image_5_path),
-
-    #     gr.update(value=status),
-
-    #     gr.update(value=""),                                          
-
-    #     gr.update(value=5), gr.update(value=5), gr.update(value=5), gr.update(value=5), gr.update(value=5),
-
-    #     gr.update(value=None),                                        
-
-    # )
-
-
-
-
 
 def to_thanks(name: str, user_seen: List[str], samples: List[Sample]):
-
-    # Calculate how many are left based on the updated seen list
-
     left = user_left_count(user_seen, samples)
-
     target = user_target_count(samples)
-
     if left > 0:
-
-            # Message for users who are leaving early
-
-            msg = (
-
+        msg = (
             f"### ⏸️ Session Paused!\n\n"
-
             f"### ✅ Thanks, {name}! Your progress has been saved.\n\n"
-
-                f"We’re grateful for your time and expertise. Our suggested target is "
-
-                f"{TARGET_PER_PERSON} images per reviewer"
-
-                f"You have **{left}** images left.\n\n"
-
-                f"You can close this tab and return whenever you like—just use the same Name and Email to **continue where you left off**.\n\n"
-
-                f"If you have questions, issues, or suggestions, please email **{CONTACT_EMAIL}**.\n\n"
-
-                f"Click **Start Again** to evaluate another image."
-
+            f"We’re grateful for your time and expertise. Our suggested target is "
+            f"{TARGET_PER_PERSON} images per reviewer.\n\n"
+            f"You have **{left}** images left.\n\n"
+            f"You can close this tab and return whenever you like—just use the same Name and Email to **continue where you left off**.\n\n"
+            f"If you have questions, issues, or suggestions, please email **{CONTACT_EMAIL}**.\n\n"
+            f"Click **Start Again** to evaluate another image."
         )
-
     else:
-
-        # Message for users who completed the target
-
         msg = (
-
             f"### ✅ All Done, {name}!\n\n"
-
             f"You’ve completed the target of **{target}** images. Your responses are securely saved.\n\n"
-
             f"We’re extremely grateful for your time and expertise. You are welcome to continue with more images if you wish, or you can finish here.\n\n"
-
             f"If you have questions, issues, or suggestions, please email **{CONTACT_EMAIL}**.\n\n"
-
         )
-
     return gr.update(visible=False), gr.update(visible=True), gr.update(value=msg)
 
-
-
 def hide_thanks():
-
     return gr.update(visible=False)
 
-
-
 def maybe_show_thanks(name: str, seen: List[str], samples: List[Sample]):
-
-    # Check if the user has reached the target
-
     if len(set(seen or [])) >= TARGET_PER_PERSON:
-
         return to_thanks(name, seen, samples)
-
-    
-
-    # If not done, keep evaluation panel visible
-
     return gr.update(visible=True), gr.update(visible=False), gr.update()
 
-    
-
 def reset_to_start():
-
-    """
-
-    Clears inputs and resets the view to the login page.
-
-    """
-
     return (
-
         gr.update(value=""), # Clear Name
-
         gr.update(value=""), # Clear Email
-
         gr.update(visible=True), # Show Start Group
-
         gr.update(visible=True), # Show Intro
-
         gr.update(visible=False), # Hide Eval
-
         gr.update(visible=False), # Hide Thanks
-
     )
 
-
-
 # ----------------------
-
 # UI
-
 # ----------------------
-
 with gr.Blocks(title="RTS Human Evaluation", theme=gr.themes.Soft()) as demo:
-
     intro_md = gr.Markdown(
-
     f"""
-
     # Retrogressive Thaw Slump (RTS) Human Evaluation
 
-
-
     ### 👋 Welcome, and thanks for lending your expertise!
-
     We’re inviting domain experts to help evaluate satellite image patches for RTS.
 
-  
-
     ---
 
-
-
     ### 📋 Instructions
-
     * **Suggested target:** ~{TARGET_PER_PERSON} images per reviewer.
-
     * **The Task:** For each set, you will see 5 variations of the same satellite image.
-
     * **Rating:** Rate each image from **1 (Poor)** to **10 (Excellent)** based on how clearly the RTS feature (indicated by the **Red Box**) is depicted.
 
-    
-
     ### ⏸️ Saving & Resuming
-
     * **Automatic Saving:** Your progress is saved automatically after every "Submit".
-
     * **Take a Break:** You can close this tab at any time.
-
     * **How to Resume:** Simply return here and enter the **exact same Name and Email**. The system will pick up exactly where you left off.
 
-
-
     ---
-
     **Questions or issues?** Email **{CONTACT_EMAIL}** — we appreciate your feedback and suggestions.
 
-    
-
     **Ready?** Enter your details below to begin.
-
     """
-
     )
 
-
-
     # Hidden states
-
     state_uid = gr.State("")
-
     state_samples = gr.State([])
-
     state_seen = gr.State([])
-
     state_idx = gr.State(-1)
 
-
-
     with gr.Group() as start_group:
-
         with gr.Row():
-
             name = gr.Textbox(label="Full name", placeholder="Jane Doe", autofocus=True)
-
             email = gr.Textbox(label="Email address", placeholder="jane@example.com")
-
             start_btn = gr.Button("Start / Resume", variant="primary")
-
         status = gr.Markdown("\n")
 
-
-
     eval_panel = gr.Group(visible=False)
-
     with eval_panel:
-
-        
-
-        # --- NEW LAYOUT: 5 COLUMNS, 1-10 SLIDERS ---
-
         gr.Markdown(
-
             """
-
             Focus your attention on the area inside the **Red Box**. This marks the potential location of the Retrogressive Thaw Slump (RTS). Compare the five images below. Rate how clearly and accurately each image depicts the **RTS** feature.
 
-            
-
             **Rating Scale (1 - 10):**
-
             * **10 (Excellent):** The RTS feature is sharp, distinct, and clearly visible.
-
             * **1 (Poor):** The RTS feature is blurry, distorted, or impossible to distinguish.
-
             """
-
         )
 
-        
-
         with gr.Row():
-
             with gr.Column(scale=1, min_width=150):
-
                 gr.Markdown("<div style='text-align:center; font-weight:600;'>Image 1</div>")
-
                 image_1 = gr.Image(show_label=False, interactive=False, height=256, show_download_button=False)
-
                 score_1 = gr.Slider(minimum=1, maximum=10, step=1, value=5, label="Score (1-10)")
 
-                
-
             with gr.Column(scale=1, min_width=150):
-
                 gr.Markdown("<div style='text-align:center; font-weight:600;'>Image 2</div>")
-
                 image_2 = gr.Image(show_label=False, interactive=False, height=256, show_download_button=False)
-
                 score_2 = gr.Slider(minimum=1, maximum=10, step=1, value=5, label="Score (1-10)")
 
-                
-
             with gr.Column(scale=1, min_width=150):
-
                 gr.Markdown("<div style='text-align:center; font-weight:600;'>Image 3</div>")
-
                 image_3 = gr.Image(show_label=False, interactive=False, height=256, show_download_button=False)
-
                 score_3 = gr.Slider(minimum=1, maximum=10, step=1, value=5, label="Score (1-10)")
 
-                
-
             with gr.Column(scale=1, min_width=150):
-
                 gr.Markdown("<div style='text-align:center; font-weight:600;'>Image 4</div>")
-
                 image_4 = gr.Image(show_label=False, interactive=False, height=256, show_download_button=False)
-
                 score_4 = gr.Slider(minimum=1, maximum=10, step=1, value=5, label="Score (1-10)")
 
-            
-
             with gr.Column(scale=1, min_width=150):
-
                 gr.Markdown("<div style='text-align:center; font-weight:600;'>Image 5</div>")
-
                 image_5 = gr.Image(show_label=False, interactive=False, height=256, show_download_button=False)
-
                 score_5 = gr.Slider(minimum=1, maximum=10, step=1, value=5, label="Score (1-10)")
 
-
-
         notes_q1 = gr.Textbox(
-
             label="Notes (Optional)",
-
             lines=2,
-
             placeholder="If there are multiple RTS or ambiguities, please note here."
-
         )
 
-        
-
         with gr.Row():
-
             submit_next_btn = gr.Button("Submit & Next Image", variant="primary")
-
             pause_exit_btn = gr.Button("Exit", variant="secondary")
 
-
-
-        # your_jsonl_path = gr.Textbox(label="Your results file path (for reference)", interactive=False)
-
         your_jsonl_path = gr.State()
 
     with gr.Group(visible=False) as thanks_group:
-
         thanks_md = gr.Markdown("### ✅ Thanks! Your responses were saved.\n\nClick **Start Again** to evaluate another image.")
-
         restart_btn = gr.Button("Start Again", variant="primary")
 
-
-
     # --- Wiring ---
-
-
-
     start_event = start_btn.click(
-
         start_or_resume,
-
         inputs=[name, email],
-
         outputs=[
-
             state_uid, state_samples, state_seen, state_idx,
-
             image_1, image_2, image_3, image_4, image_5,
-
             status, your_jsonl_path,
-
             eval_panel, intro_md, start_group
-
         ],
-
     )
-
     start_event.then(hide_thanks, inputs=None, outputs=[thanks_group])
 
-
-
     # 1. When Pause is clicked, just pass the state through
-
     pause_event = pause_exit_btn.click(
-
         pause_exit,
-
         inputs=[state_seen, state_samples],
-
         outputs=[state_seen, state_samples],
-
     )
 
-    
-
     # 2. Then show the "Thanks/Resume" screen with the 'how many left' message
-
     pause_event.then(
-
         to_thanks,
-
         inputs=[name, state_seen, state_samples],
-
         outputs=[eval_panel, thanks_group, thanks_md],
-
     )
 
-
-
     nextimg_event = submit_next_btn.click(
-
         submit_next_image,
-
         inputs=[name, email, state_uid, state_samples, state_seen, state_idx,
-
                 score_1, score_2, score_3, score_4, score_5, notes_q1],
-
         outputs=[state_seen, state_idx,
-
                 image_1, image_2, image_3, image_4, image_5,
-
                 status, notes_q1,
-
                 score_1, score_2, score_3, score_4, score_5],
-
     )
-
     nextimg_event.then(
-
         maybe_show_thanks,
-
         inputs=[name, state_seen, state_samples],
-
         outputs=[eval_panel, thanks_group, thanks_md],
-
     )
 
-
-
-    # --- CHANGED: Calls reset_to_start instead of start_or_resume ---
-
     restart_event = restart_btn.click(
-
         reset_to_start,
-
         inputs=[],
-
         outputs=[
-
             name, email,
-
             start_group, intro_md,
-
             eval_panel, thanks_group
-
         ],
-
     )
 
-
-
 if __name__ == "__main__":
-
-    # --- DYNAMIC READ FROM HF_RESULTS_REPO ---
-
     if HF_RESULTS_REPO:
-
         from huggingface_hub import snapshot_download
-
-        # print(f"Reading images and metadata from: {HF_RESULTS_REPO}...")
-
         try:
-
-            # This pulls your repo's 'data' folder into the current workspace
-
             snapshot_download(
-
                 repo_id=HF_RESULTS_REPO,
-
                 repo_type="dataset",
-
-                local_dir=".",            
-
+                local_dir=".",
                 allow_patterns=["data/*", "results/*"],
-
                 token=HF_TOKEN
-
             )
-
         except Exception as e:
-
             print(f"Error reading from HF: {e}")
 
-
-
     ensure_paths()
-
-    # Pre-check dataset load from the newly downloaded files
-
     _ = load_dataset(CAPTIONS_JSON_PATH, GT_MASKED_DIR, GT_UNMASKED_DIR, SR_DIR, ORIGINAL_DIR, IMAGE_5_DIR)
 
-    
-
-    print("✅ Successfully synced with HF Repo. Launching app.")
-
+    print("✅ Launching app.")
     demo.queue()
-
-    demo.launch()
+    demo.launch()