Support Gradio file paths for uploads

frame_extraction/src/frame_extraction/app.py

@@ -6,7 +6,7 @@ import os
 import shutil
 import uuid
 from pathlib import Path
-from typing import Any, Tuple
+from typing import Any, Iterable, Tuple
 
 import gradio as gr
 import numpy as np
@@ -28,6 +28,16 @@ def ensure_output_dirs() -> None:
     (OUTPUT_DIR / "frames").mkdir(parents=True, exist_ok=True)
 
 
+def _resolve_file_path(entry: gr.FileData | str | Path) -> Path:
+    if isinstance(entry, Path):
+        return entry
+    if isinstance(entry, gr.FileData):
+        return Path(entry.name)
+    if isinstance(entry, str):
+        return Path(entry)
+    raise ValueError(f"Unsupported file type: {type(entry)!r}")
+
+
 def summarize_catalog(catalog_path: Path) -> Tuple[str, list[dict[str, Any]], list[list[str]]]:
     if not catalog_path.exists():
         return ("Catalog not found.", [], [])
@@ -51,31 +61,32 @@ def summarize_catalog(catalog_path: Path) -> Tuple[str, list[dict[str, Any]], li
     return message, index, gallery
 
 
-def build_catalog_from_video(files: list[gr.FileData]) -> tuple[str | None, str, list[dict[str, Any]], list[list[str]], list[dict[str, Any]], list[list[str]]]:
+def build_catalog_from_video(files: list[gr.FileData | str | Path]) -> tuple[str | None, str, list[dict[str, Any]], list[list[str]], list[dict[str, Any]], list[list[str]]]:
     if not files:
         raise gr.Error("Please upload a source video first.")
 
     ensure_output_dirs()
-    file = files[0]
+    source_path = _resolve_file_path(files[0])
+    if not source_path.exists():
+        raise gr.Error(f"Uploaded video not found: {source_path}")
+
     run_id = uuid.uuid4().hex[:8]
     video_dir = OUTPUT_DIR / "videos"
-    video_path = video_dir / f"{run_id}_{Path(file.name).name}"
-    shutil.copy(file.name, video_path)
+    video_path = video_dir / f"{run_id}_{source_path.name}"
+    shutil.copy(source_path, video_path)
 
     catalog_dir = OUTPUT_DIR / "catalogs" / f"catalog_{run_id}"
     cfg = CatalogConfig(video_path=video_path, output_dir=catalog_dir)
     catalog_path = build_catalog(cfg)
     message, index, gallery = summarize_catalog(catalog_path)
-    # When a new catalog is generated, clear existing matches display
     empty_matches: list[dict[str, Any]] = []
     empty_gallery: list[list[str]] = []
     return str(catalog_path), message, index, gallery, empty_matches, empty_gallery
 
 
-def predict_from_arrays(files: list[gr.FileData], catalog_path: str | None) -> tuple[list[dict[str, Any]], list[list[str]]]:
+def predict_from_files(files: list[gr.FileData | str | Path], catalog_path: str | None) -> tuple[list[dict[str, Any]], list[list[str]]]:
     if not catalog_path:
         raise gr.Error("Catalog not ready yet. Upload a video first.")
-
     if not files:
         raise gr.Error("Please upload at least one frame.")
 
@@ -85,8 +96,9 @@ def predict_from_arrays(files: list[gr.FileData], catalog_path: str | None) -> t
     frames_dir.mkdir(parents=True, exist_ok=True)
 
     arrays: list[np.ndarray] = []
-    for idx, file in enumerate(files):
-        array = np.array(Image.open(file.name).convert("RGB"))
+    for idx, entry in enumerate(files):
+        path = _resolve_file_path(entry)
+        array = np.array(Image.open(path).convert("RGB"))
         arrays.append(array)
         Image.fromarray(array).save(frames_dir / f"upload_{idx:03d}.png")
 
@@ -147,7 +159,7 @@ def build_interface() -> gr.Blocks:
         )
 
         frame_upload.upload(
-            predict_from_arrays,
+            predict_from_files,
             inputs=[frame_upload, catalog_state],
             outputs=[matches_json, match_gallery],
         )