add tabs and links

app.py

@@ -33,20 +33,20 @@ def restart_space():
     API.restart_space(repo_id=REPO_ID)
 
 ### Space initialisation
-try:
-    print(EVAL_REQUESTS_PATH)
-    snapshot_download(
-        repo_id=QUEUE_REPO, local_dir=EVAL_REQUESTS_PATH, repo_type="dataset", tqdm_class=None, etag_timeout=30, token=TOKEN
-    )
-except Exception:
-    restart_space()
-try:
-    print(EVAL_RESULTS_PATH)
-    snapshot_download(
-        repo_id=RESULTS_REPO, local_dir=EVAL_RESULTS_PATH, repo_type="dataset", tqdm_class=None, etag_timeout=30, token=TOKEN
-    )
-except Exception:
-    restart_space()
+# try:
+#     print(EVAL_REQUESTS_PATH)
+#     snapshot_download(
+#         repo_id=QUEUE_REPO, local_dir=EVAL_REQUESTS_PATH, repo_type="dataset", tqdm_class=None, etag_timeout=30, token=TOKEN
+#     )
+# except Exception:
+#     restart_space()
+# try:
+#     print(EVAL_RESULTS_PATH)
+#     snapshot_download(
+#         repo_id=RESULTS_REPO, local_dir=EVAL_RESULTS_PATH, repo_type="dataset", tqdm_class=None, etag_timeout=30, token=TOKEN
+#     )
+# except Exception:
+#     restart_space()
 
 
 LEADERBOARD_DF = get_leaderboard_df(EVAL_RESULTS_PATH, EVAL_REQUESTS_PATH, COLS, BENCHMARK_COLS)
@@ -96,7 +96,10 @@ with demo:
 
     with gr.Tabs(elem_classes="tab-buttons") as tabs:
         with gr.TabItem("🏅 Detector Leaderboard", elem_id="detector-benchmark-tab-table", id=0):
-            leaderboard = init_leaderboard(LEADERBOARD_DF)
+            with gr.TabItem("Generated Image Detection", elem_id="detector-benchmark-tab-table-1", id=3):
+                leaderboard = init_leaderboard(LEADERBOARD_DF)
+            with gr.TabItem("In-n-out-painting Detection", elem_id="detector-benchmark-tab-table-2", id=4):
+                leaderboard = init_leaderboard(LEADERBOARD_DF)
 
         with gr.TabItem("🔍 Detector Playground ", elem_id="detector-playground-tab-table", id=1):
             with gr.Row():

eval-results/demo-leaderboard/DE-FAKE/results.json

@@ -1,10 +1,11 @@
 {
     "config": {
-        "model_name": "DE-FAKE"
+        "model_name": "DE-FAKE",
+        "model_link": "https://github.com/zeyangsha/De-Fake/tree/main"
     },
     "results": {
         "miragenews": {
-            "acc": 0
+            "acc": 0.55
         },
         "genimage": {
             "acc": 0.90

eval-results/demo-leaderboard/DIRE/results.json

@@ -1,13 +1,14 @@
 {
     "config": {
-        "model_name": "DIRE"
+        "model_name": "DIRE",
+        "model_link": "https://github.com/ZhendongWang6/DIRE"
     },
     "results": {
         "miragenews": {
-            "acc": 0
+            "acc": 0.87
         },
         "genimage": {
-            "acc": 0.90
+            "acc": 0.68
         }
     }
 }

eval-results/demo-leaderboard/Universal/results.json

@@ -1,13 +1,14 @@
 {
     "config": {
-        "model_name": "Universal"
+        "model_name": "UniversalFakeDetect",
+        "model_link": "https://utkarshojha.github.io/universal-fake-detection/"
     },
     "results": {
         "miragenews": {
-            "acc": 0
+            "acc": 0.42
         },
         "genimage": {
-            "acc": 0.90
+            "acc": 0.73
         }
     }
 }

src/display/formatting.py

@@ -1,5 +1,5 @@
 def model_hyperlink(link, model_name):
-    return f'<a target="_blank" href="{link}" style="color: var(--link-text-color); text-decoration: underline;text-decoration-style: dotted;">{model_name}</a>'
+    return f'<a target="_blank" href="{link}" style="color: var(--link-text-color); text-decoration: underline;text-decoration-style: dotted;">{model_name}</a>' if link else model_name
 
 
 def make_clickable_model(model_name):

src/leaderboard/read_evals.py

@@ -7,7 +7,7 @@ from dataclasses import dataclass
 import dateutil
 import numpy as np
 
-from src.display.formatting import make_clickable_model
+from src.display.formatting import model_hyperlink
 from src.display.utils import AutoEvalColumn, ModelType, Tasks, Precision, WeightType
 from src.submission.check_validity import is_model_on_hub
 
@@ -20,6 +20,7 @@ class EvalResult:
     full_model: str # org/model (path on hub)
     org: str 
     model: str
+    model_link: str
     # revision: str # commit hash, "" if main
     results: dict
     # precision: Precision = Precision.Unknown
@@ -57,14 +58,15 @@ class EvalResult:
             result_key = f"{org}_{model}"
         full_model = "/".join(org_and_model)
 
-        still_on_hub, _, model_config = is_model_on_hub(
-            full_model, config.get("model_sha", "main"), trust_remote_code=True, test_tokenizer=False
-        )
-        architecture = "?"
-        if model_config is not None:
-            architectures = getattr(model_config, "architectures", None)
-            if architectures:
-                architecture = ";".join(architectures)
+        model_link = config.get("model_link", None)
+        # still_on_hub, _, model_config = is_model_on_hub(
+        #     full_model, config.get("model_sha", "main"), trust_remote_code=True, test_tokenizer=False
+        # )
+        # architecture = "?"
+        # if model_config is not None:
+        #     architectures = getattr(model_config, "architectures", None)
+        #     if architectures:
+        #         architecture = ";".join(architectures)
 
         # Extract results available in this file (some results are split in several files)
         results = {}
@@ -82,6 +84,7 @@ class EvalResult:
         return self(
             eval_name=result_key,
             full_model=full_model,
+            model_link=model_link,
             org=org,
             model=model,
             results=results,
@@ -91,21 +94,21 @@ class EvalResult:
             # architecture=architecture
         )
 
-    def update_with_request_file(self, requests_path):
-        """Finds the relevant request file for the current model and updates info with it"""
-        request_file = get_request_file_for_model(requests_path, self.full_model)
-
-        try:
-            with open(request_file, "r") as f:
-                request = json.load(f)
-            self.model_type = ModelType.from_str(request.get("model_type", ""))
-            self.weight_type = WeightType[request.get("weight_type", "Original")]
-            self.license = request.get("license", "?")
-            self.likes = request.get("likes", 0)
-            self.num_params = request.get("params", 0)
-            self.date = request.get("submitted_time", "")
-        except Exception:
-            print(f"Could not find request file for {self.org}/{self.model} with precision {self.precision.value.name}")
+    # def update_with_request_file(self, requests_path):
+    #     """Finds the relevant request file for the current model and updates info with it"""
+    #     request_file = get_request_file_for_model(requests_path, self.full_model)
+
+    #     try:
+    #         with open(request_file, "r") as f:
+    #             request = json.load(f)
+    #         self.model_type = ModelType.from_str(request.get("model_type", ""))
+    #         self.weight_type = WeightType[request.get("weight_type", "Original")]
+    #         self.license = request.get("license", "?")
+    #         self.likes = request.get("likes", 0)
+    #         self.num_params = request.get("params", 0)
+    #         self.date = request.get("submitted_time", "")
+    #     except Exception:
+    #         print(f"Could not find request file for {self.org}/{self.model} with precision {self.precision.value.name}")
 
     def to_dict(self):
         """Converts the Eval Result to a dict compatible with our dataframe display"""
@@ -117,7 +120,7 @@ class EvalResult:
             # AutoEvalColumn.model_type_symbol.name: self.model_type.value.symbol,
             # AutoEvalColumn.weight_type.name: self.weight_type.value.name,
             # AutoEvalColumn.architecture.name: self.architecture,
-            AutoEvalColumn.model.name: make_clickable_model(self.full_model),
+            AutoEvalColumn.model.name: model_hyperlink(self.model_link, self.full_model),
             # AutoEvalColumn.revision.name: self.revision,
             AutoEvalColumn.average.name: average,
             # AutoEvalColumn.license.name: self.license,
@@ -130,26 +133,26 @@ class EvalResult:
         return data_dict
 
 
-def get_request_file_for_model(requests_path, model_name):
-    """Selects the correct request file for a given model. Only keeps runs tagged as FINISHED"""
-    request_files = os.path.join(
-        requests_path,
-        f"{model_name}_eval_request_*.json",
-    )
-    request_files = glob.glob(request_files)
-
-    # Select correct request file (precision)
-    request_file = ""
-    request_files = sorted(request_files, reverse=True)
-    for tmp_request_file in request_files:
-        with open(tmp_request_file, "r") as f:
-            req_content = json.load(f)
-            if (
-                req_content["status"] in ["FINISHED"]
-                # and req_content["precision"] == precision.split(".")[-1]
-            ):
-                request_file = tmp_request_file
-    return request_file
+# def get_request_file_for_model(requests_path, model_name):
+#     """Selects the correct request file for a given model. Only keeps runs tagged as FINISHED"""
+#     request_files = os.path.join(
+#         requests_path,
+#         f"{model_name}_eval_request_*.json",
+#     )
+#     request_files = glob.glob(request_files)
+
+#     # Select correct request file (precision)
+#     request_file = ""
+#     request_files = sorted(request_files, reverse=True)
+#     for tmp_request_file in request_files:
+#         with open(tmp_request_file, "r") as f:
+#             req_content = json.load(f)
+#             if (
+#                 req_content["status"] in ["FINISHED"]
+#                 # and req_content["precision"] == precision.split(".")[-1]
+#             ):
+#                 request_file = tmp_request_file
+#     return request_file
 
 
 def get_raw_eval_results(results_path: str, requests_path: str) -> list[EvalResult]: