Upload ego4d_selection

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@@ -66,3 +66,4 @@ ego4d/v2/annotations/fho_oscc-pnr_train.json filter=lfs diff=lfs merge=lfs -text
 ego4d/v2/annotations/fho_oscc-pnr_val.json filter=lfs diff=lfs merge=lfs -text
 ego4d/v2/annotations/fho_sta_train.json filter=lfs diff=lfs merge=lfs -text
 ego4d/v2/annotations/fho_sta_val.json filter=lfs diff=lfs merge=lfs -text
+ego4d_selection/ego4d_selected_clips.csv filter=lfs diff=lfs merge=lfs -text

ego4d_selection/EGO4D_TOOL_LTA_DOWNLOAD_REPORT.md

@@ -0,0 +1,44 @@
+# Ego4D Tool-Related FHO Clip Selection Report
+
+## Downloaded Data
+
+- Annotations root: `D:\ego4d_data\v2\annotations`
+- Clips root: `D:\ego4d_data\v2\clips`
+- Downloaded clips: 30 mp4 files
+- Total downloaded clip size: about 1.36 GB
+
+## Selection Strategy
+
+The selection uses Ego4D FHO Long-Term Anticipation annotations and taxonomy.
+
+It prioritizes engineering-tool nouns and verbs:
+
+- Nouns: screw, screwdriver, wrench, drill, hammer, plier, knife, scissors, ruler, saw, glue, tape, toolbox, etc.
+- Verbs: take, put, hold, hit/hammer, measure, tighten, screw, drill, loosen, repair, weld, unscrew, etc.
+
+The first batch is intentionally limited to 30 downloadable clips. This is a sanity-check subset, not the final full training set.
+
+## Important Files
+
+- Selection CSV:
+  `D:\event_driven\01_data\ego4d_selection\tool_lta_top30\ego4d_tool_lta_selected_clips.csv`
+
+- Downloadable manifest mapping:
+  `D:\event_driven\01_data\ego4d_selection\tool_lta_top30_fho_manifest\ego4d_downloadable_exported_clips.csv`
+
+- Download UID file:
+  `D:\event_driven\01_data\ego4d_selection\tool_lta_top30_fho_manifest\ego4d_exported_clip_uids.txt`
+
+- Downloaded videos:
+  `D:\ego4d_data\v2\clips\*.mp4`
+
+## What This Data Is Good For
+
+Use these clips for:
+
+- object-centric world model pretraining
+- future active object / short-term interaction prediction
+- hand-object event context
+- event-window VLM prompt examples
+
+Do not treat this as the main dataset for YOLO tool detection. For YOLO, continue using Open Images and your own tabletop tool data.

ego4d_selection/README.md

@@ -0,0 +1,66 @@
+# Ego4D Selection for Event-Driven Manipulation
+
+This folder contains scripts to download only the Ego4D parts useful for the event-driven manipulation project.
+
+## What to Download
+
+Priority:
+
+1. FHO annotations: state change, PNR, hand-object interaction, active object.
+2. FHO clips selected by tool/state-change keywords.
+
+Do not download full-scale Ego4D videos first.
+
+## Prerequisite
+
+Ego4D requires AWS credentials after license approval. Configure the default AWS profile before running the scripts.
+
+Expected failure when credentials are missing:
+
+```text
+RuntimeError: Could not find AWS profile 'default'.
+```
+
+## Step 1: Download Annotations
+
+```powershell
+powershell -ExecutionPolicy Bypass -File D:\event_driven\01_data\ego4d_selection\download_ego4d_annotations.ps1
+```
+
+Output target:
+
+```text
+D:\ego4d_data\annotations
+```
+
+## Step 2: Select and Download Clips
+
+```powershell
+powershell -ExecutionPolicy Bypass -File D:\event_driven\01_data\ego4d_selection\select_and_download_ego4d_clips.ps1
+```
+
+Selection outputs:
+
+```text
+D:\event_driven\01_data\ego4d_selection\ego4d_selected_clips.csv
+D:\event_driven\01_data\ego4d_selection\ego4d_selected_video_uids.txt
+D:\event_driven\01_data\ego4d_selection\selection_summary.json
+```
+
+Downloaded clips target:
+
+```text
+D:\ego4d_data\clips
+```
+
+## Why This Subset
+
+Ego4D is mainly useful for:
+
+- event/state-change detection
+- PNR timing
+- hand-object contact
+- short-term active object prediction
+- object-centric world model training
+
+It is not the best primary dataset for tool YOLO detection. Keep Open Images and your own tabletop data as the main YOLO training data.

ego4d_selection/configure_ego4d_aws_profile.ps1

@@ -0,0 +1,26 @@
+$ErrorActionPreference = "Stop"
+
+$python = "D:\miniconda3_qwen\envs\qwen3vl_runner\python.exe"
+$secretDir = "D:\event_driven\secrets"
+$credentialsFile = "$secretDir\aws_credentials"
+$configFile = "$secretDir\aws_config"
+
+New-Item -ItemType Directory -Force -Path $secretDir | Out-Null
+
+$env:AWS_SHARED_CREDENTIALS_FILE = $credentialsFile
+$env:AWS_CONFIG_FILE = $configFile
+
+Write-Host "Configuring AWS profile 'ego4d' in:"
+Write-Host "  credentials: $credentialsFile"
+Write-Host "  config:      $configFile"
+Write-Host "Do not paste credentials into chat. Enter them only in this terminal prompt."
+
+& $python -m awscli configure --profile ego4d
+if ($LASTEXITCODE -ne 0) {
+    throw "aws configure failed"
+}
+
+& $python -m awscli configure list --profile ego4d
+if ($LASTEXITCODE -ne 0) {
+    throw "aws configure list failed"
+}

ego4d_selection/download_ego4d_annotations.ps1

@@ -0,0 +1,20 @@
+$ErrorActionPreference = "Stop"
+
+$ego4d = "D:\miniconda3_qwen\envs\qwen3vl_runner\Scripts\ego4d.exe"
+$out = "D:\ego4d_data"
+$env:AWS_SHARED_CREDENTIALS_FILE = "D:\event_driven\secrets\aws_credentials"
+$env:AWS_CONFIG_FILE = "D:\event_driven\secrets\aws_config"
+
+New-Item -ItemType Directory -Force -Path $out | Out-Null
+
+& $ego4d `
+  --output_directory $out `
+  --datasets annotations `
+  --benchmarks FHO `
+  --aws_profile_name ego4d `
+  --metadata `
+  -y
+
+if ($LASTEXITCODE -ne 0) {
+    throw "Ego4D annotation download failed. Check AWS profile/license credentials."
+}

ego4d_selection/ego4d_map_selected_to_exported_clips.py

@@ -0,0 +1,80 @@
+#!/usr/bin/env python3
+"""Map selected FHO annotation clip_uids to downloadable exported_clip_uids."""
+
+from __future__ import annotations
+
+import argparse
+import csv
+import json
+from pathlib import Path
+
+
+def read_csv(path: Path) -> list[dict[str, str]]:
+    with path.open("r", encoding="utf-8-sig", newline="") as f:
+        return list(csv.DictReader(f))
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--selected-csv", type=Path, required=True)
+    parser.add_argument("--manifest-csv", type=Path, default=Path(r"D:\ego4d_data\v2\clips\manifest.csv"))
+    parser.add_argument("--out-dir", type=Path, required=True)
+    parser.add_argument("--max-exported-clips", type=int, default=30)
+    args = parser.parse_args()
+
+    selected = read_csv(args.selected_csv)
+    selected_clip_uids = {row["clip_uid"] for row in selected if row.get("clip_uid")}
+    selected_video_uids = {row["video_uid"] for row in selected if row.get("video_uid")}
+
+    manifest_rows = read_csv(args.manifest_csv)
+    matched: list[dict[str, str]] = []
+    seen_exported: set[str] = set()
+    for row in manifest_rows:
+        parent_clip_uid = row.get("parent_clip_uid", "")
+        parent_video_uid = row.get("parent_video_uid", "")
+        exported_clip_uid = row.get("exported_clip_uid", "")
+        if not exported_clip_uid or exported_clip_uid in seen_exported:
+            continue
+        benchmarks = str(row.get("benchmarks", "")).lower()
+        if "fho" not in benchmarks:
+            continue
+        if parent_clip_uid in selected_clip_uids or parent_video_uid in selected_video_uids:
+            matched.append(row)
+            seen_exported.add(exported_clip_uid)
+        if len(matched) >= args.max_exported_clips:
+            break
+
+    args.out_dir.mkdir(parents=True, exist_ok=True)
+    out_csv = args.out_dir / "ego4d_downloadable_exported_clips.csv"
+    if matched:
+        with out_csv.open("w", encoding="utf-8-sig", newline="") as f:
+            writer = csv.DictWriter(f, fieldnames=list(matched[0].keys()))
+            writer.writeheader()
+            writer.writerows(matched)
+    else:
+        out_csv.write_text("", encoding="utf-8")
+
+    uid_file = args.out_dir / "ego4d_exported_clip_uids.txt"
+    uid_file.write_text(
+        "\n".join(row["exported_clip_uid"] for row in matched) + ("\n" if matched else ""),
+        encoding="utf-8",
+    )
+
+    summary = {
+        "selected_annotation_rows": len(selected),
+        "selected_clip_uids": len(selected_clip_uids),
+        "selected_video_uids": len(selected_video_uids),
+        "matched_exported_clips": len(matched),
+        "max_exported_clips": args.max_exported_clips,
+        "uid_file": str(uid_file),
+        "csv": str(out_csv),
+    }
+    (args.out_dir / "downloadable_clip_summary.json").write_text(
+        json.dumps(summary, ensure_ascii=False, indent=2),
+        encoding="utf-8",
+    )
+    print(json.dumps(summary, ensure_ascii=False, indent=2))
+
+
+if __name__ == "__main__":
+    main()

ego4d_selection/ego4d_select_fho_tool_lta.py

@@ -0,0 +1,164 @@
+#!/usr/bin/env python3
+"""Select Ego4D FHO LTA clips with engineering-tool nouns/verbs."""
+
+from __future__ import annotations
+
+import argparse
+import csv
+import json
+from collections import Counter
+from pathlib import Path
+from typing import Any
+
+
+TOOL_NOUN_TERMS = [
+    "awl",
+    "axe",
+    "bat_(tool)",
+    "bolt_extractor",
+    "caliper",
+    "cutter_(tool)",
+    "drill_",
+    "drill_bit",
+    "file_(tool)",
+    "glue_",
+    "glue_gun",
+    "hammer_",
+    "jack_(tool)",
+    "knife_",
+    "nail_gun",
+    "nut_(tool)",
+    "plier",
+    "ruler_",
+    "saw_",
+    "scissors",
+    "screw_",
+    "screwdriver",
+    "set_square",
+    "tape_",
+    "tape_measure",
+    "toolbox",
+    "wrench_",
+]
+
+TOOL_VERB_TERMS = [
+    "drill",
+    "file_(with_tool)",
+    "hammer",
+    "screw",
+    "stick_(tape",
+    "unscrew",
+    "tighten",
+    "loosen",
+    "repair",
+    "weld",
+    "measure_",
+]
+
+
+def load_json(path: Path) -> Any:
+    with path.open("r", encoding="utf-8") as f:
+        return json.load(f)
+
+
+def matches_any(text: str, terms: list[str]) -> bool:
+    lower = text.lower()
+    return any(term in lower for term in terms)
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--annotations-root", type=Path, default=Path(r"D:\ego4d_data\v2\annotations"))
+    parser.add_argument("--out-dir", type=Path, default=Path(r"D:\event_driven\01_data\ego4d_selection\tool_lta"))
+    parser.add_argument("--max-video-uids", type=int, default=120)
+    parser.add_argument("--min-actions-per-video", type=int, default=1)
+    args = parser.parse_args()
+
+    files = [
+        args.annotations_root / "fho_lta_train.json",
+        args.annotations_root / "fho_lta_val.json",
+    ]
+    for path in files:
+        if not path.exists():
+            raise FileNotFoundError(path)
+
+    selected: list[dict[str, Any]] = []
+    for path in files:
+        data = load_json(path)
+        for row in data.get("clips", []):
+            noun = str(row.get("noun", ""))
+            verb = str(row.get("verb", ""))
+            noun_match = matches_any(noun, TOOL_NOUN_TERMS)
+            verb_match = matches_any(verb, TOOL_VERB_TERMS)
+            if not noun_match and not verb_match:
+                continue
+            selected.append(
+                {
+                    "source_file": str(path),
+                    "split": data.get("split", ""),
+                    "video_uid": row.get("video_uid", ""),
+                    "clip_uid": row.get("clip_uid", ""),
+                    "clip_parent_start_sec": row.get("clip_parent_start_sec", ""),
+                    "clip_parent_end_sec": row.get("clip_parent_end_sec", ""),
+                    "action_clip_start_sec": row.get("action_clip_start_sec", ""),
+                    "action_clip_end_sec": row.get("action_clip_end_sec", ""),
+                    "verb": verb,
+                    "verb_label": row.get("verb_label", ""),
+                    "noun": noun,
+                    "noun_label": row.get("noun_label", ""),
+                    "match_type": "noun+verb" if noun_match and verb_match else ("noun" if noun_match else "verb"),
+                }
+            )
+
+    video_counts = Counter(row["video_uid"] for row in selected if row["video_uid"])
+    ranked_video_uids = [
+        video_uid
+        for video_uid, count in video_counts.most_common()
+        if count >= args.min_actions_per_video
+    ][: args.max_video_uids]
+    keep = set(ranked_video_uids)
+    selected = [row for row in selected if row["video_uid"] in keep]
+
+    args.out_dir.mkdir(parents=True, exist_ok=True)
+    csv_path = args.out_dir / "ego4d_tool_lta_selected_clips.csv"
+    fieldnames = [
+        "source_file",
+        "split",
+        "video_uid",
+        "clip_uid",
+        "clip_parent_start_sec",
+        "clip_parent_end_sec",
+        "action_clip_start_sec",
+        "action_clip_end_sec",
+        "verb",
+        "verb_label",
+        "noun",
+        "noun_label",
+        "match_type",
+    ]
+    with csv_path.open("w", encoding="utf-8-sig", newline="") as f:
+        writer = csv.DictWriter(f, fieldnames=fieldnames)
+        writer.writeheader()
+        writer.writerows(selected)
+
+    uid_path = args.out_dir / "ego4d_tool_lta_video_uids.txt"
+    uid_path.write_text("\n".join(ranked_video_uids) + ("\n" if ranked_video_uids else ""), encoding="utf-8")
+
+    summary = {
+        "selected_actions": len(selected),
+        "selected_video_uids": len(ranked_video_uids),
+        "max_video_uids": args.max_video_uids,
+        "csv": str(csv_path),
+        "video_uid_file": str(uid_path),
+        "top_nouns": Counter(row["noun"] for row in selected).most_common(30),
+        "top_verbs": Counter(row["verb"] for row in selected).most_common(30),
+    }
+    (args.out_dir / "selection_summary.json").write_text(
+        json.dumps(summary, ensure_ascii=False, indent=2),
+        encoding="utf-8",
+    )
+    print(json.dumps(summary, ensure_ascii=False, indent=2))
+
+
+if __name__ == "__main__":
+    main()

ego4d_selection/ego4d_select_for_event_driven.py

@@ -0,0 +1,239 @@
+#!/usr/bin/env python3
+"""Select Ego4D clips useful for event-driven tool manipulation experiments.
+
+The script scans downloaded Ego4D annotation JSON files and extracts candidate
+video/clips for:
+  - hand-object interaction
+  - object state change
+  - short-term active object anticipation
+  - tool-like nouns/classes
+
+It is intentionally schema-tolerant because Ego4D annotation files differ by
+benchmark version.
+"""
+
+from __future__ import annotations
+
+import argparse
+import csv
+import json
+from pathlib import Path
+from typing import Any
+
+
+DEFAULT_KEYWORDS = {
+    "hammer",
+    "screwdriver",
+    "screw",
+    "nail",
+    "pliers",
+    "wrench",
+    "drill",
+    "saw",
+    "knife",
+    "scissors",
+    "tool",
+    "wood",
+    "board",
+    "tape",
+    "glue",
+    "ruler",
+    "box",
+    "cup",
+    "bottle",
+}
+
+STATE_CHANGE_HINTS = {
+    "state",
+    "change",
+    "pnr",
+    "pre",
+    "post",
+    "contact",
+    "bbox",
+    "object",
+    "noun",
+    "verb",
+}
+
+
+def iter_json_files(root: Path, include_patterns: list[str]) -> list[Path]:
+    files = sorted(root.rglob("*.json"))
+    if not include_patterns:
+        return files
+    out: list[Path] = []
+    for path in files:
+        name = path.name.lower()
+        if any(pattern.lower() in name for pattern in include_patterns):
+            out.append(path)
+    return out
+
+
+def load_json(path: Path) -> Any:
+    with path.open("r", encoding="utf-8") as f:
+        return json.load(f)
+
+
+def flatten_text(value: Any, limit: int = 12000) -> str:
+    chunks: list[str] = []
+
+    def visit(node: Any) -> None:
+        if sum(len(x) for x in chunks) > limit:
+            return
+        if isinstance(node, dict):
+            for key, item in node.items():
+                chunks.append(str(key))
+                visit(item)
+        elif isinstance(node, list):
+            for item in node[:200]:
+                visit(item)
+        elif isinstance(node, (str, int, float, bool)):
+            chunks.append(str(node))
+
+    visit(value)
+    return " ".join(chunks).lower()
+
+
+def find_values_by_key(value: Any, wanted: set[str]) -> list[str]:
+    out: list[str] = []
+
+    def visit(node: Any) -> None:
+        if isinstance(node, dict):
+            for key, item in node.items():
+                if key.lower() in wanted and item is not None:
+                    out.append(str(item))
+                visit(item)
+        elif isinstance(node, list):
+            for item in node:
+                visit(item)
+
+    visit(value)
+    return out
+
+
+def iter_records(value: Any) -> list[dict[str, Any]]:
+    records: list[dict[str, Any]] = []
+
+    def visit(node: Any) -> None:
+        if isinstance(node, dict):
+            keys = {str(k).lower() for k in node}
+            if keys & {"video_uid", "clip_uid", "clip_id", "annotation_uid"}:
+                records.append(node)
+            for item in node.values():
+                visit(item)
+        elif isinstance(node, list):
+            for item in node:
+                visit(item)
+
+    visit(value)
+    return records
+
+
+def score_record(record: dict[str, Any], keywords: set[str]) -> tuple[int, list[str]]:
+    text = flatten_text(record)
+    hits = sorted([kw for kw in keywords if kw in text])
+    score = 0
+    score += 5 * len(hits)
+    score += 2 * sum(1 for hint in STATE_CHANGE_HINTS if hint in text)
+    if "bbox" in text or "bounding" in text:
+        score += 3
+    if "pnr" in text:
+        score += 3
+    if "pre" in text and "post" in text:
+        score += 3
+    return score, hits
+
+
+def first_value(record: dict[str, Any], keys: set[str]) -> str:
+    values = find_values_by_key(record, keys)
+    return values[0] if values else ""
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--annotations-root", type=Path, default=Path(r"D:\ego4d_data\annotations"))
+    parser.add_argument("--out-dir", type=Path, default=Path(r"D:\event_driven\01_data\ego4d_selection"))
+    parser.add_argument("--min-score", type=int, default=8)
+    parser.add_argument("--keywords", nargs="*", default=sorted(DEFAULT_KEYWORDS))
+    parser.add_argument(
+        "--include-pattern",
+        nargs="*",
+        default=["fho_oscc-pnr_train", "fho_oscc-pnr_val", "fho_sta_train", "fho_sta_val"],
+        help="Filename substrings to scan. Defaults avoid huge fho_main.json.",
+    )
+    args = parser.parse_args()
+
+    if not args.annotations_root.exists():
+        raise FileNotFoundError(
+            f"annotations root not found: {args.annotations_root}. "
+            "Download Ego4D annotations first."
+        )
+
+    keywords = {x.lower() for x in args.keywords}
+    args.out_dir.mkdir(parents=True, exist_ok=True)
+
+    selected: list[dict[str, Any]] = []
+    scanned_files = iter_json_files(args.annotations_root, args.include_pattern)
+    for path in scanned_files:
+        data = load_json(path)
+        for record in iter_records(data):
+            score, hits = score_record(record, keywords)
+            if score < args.min_score:
+                continue
+            selected.append(
+                {
+                    "source_file": str(path),
+                    "score": score,
+                    "keyword_hits": ";".join(hits),
+                    "video_uid": first_value(record, {"video_uid"}),
+                    "clip_uid": first_value(record, {"clip_uid", "clip_id"}),
+                    "annotation_uid": first_value(record, {"annotation_uid", "uid"}),
+                    "noun": first_value(record, {"noun", "noun_category", "object_name"}),
+                    "verb": first_value(record, {"verb", "verb_category"}),
+                }
+            )
+
+    selected.sort(key=lambda row: (-int(row["score"]), row["source_file"], row["clip_uid"]))
+
+    csv_path = args.out_dir / "ego4d_selected_clips.csv"
+    with csv_path.open("w", encoding="utf-8-sig", newline="") as f:
+        writer = csv.DictWriter(
+            f,
+            fieldnames=[
+                "source_file",
+                "score",
+                "keyword_hits",
+                "video_uid",
+                "clip_uid",
+                "annotation_uid",
+                "noun",
+                "verb",
+            ],
+        )
+        writer.writeheader()
+        writer.writerows(selected)
+
+    video_uids = sorted({row["video_uid"] for row in selected if row["video_uid"]})
+    uid_path = args.out_dir / "ego4d_selected_video_uids.txt"
+    uid_path.write_text("\n".join(video_uids) + ("\n" if video_uids else ""), encoding="utf-8")
+
+    summary = {
+        "annotations_root": str(args.annotations_root),
+        "selected_records": len(selected),
+        "selected_video_uids": len(video_uids),
+        "min_score": args.min_score,
+        "keywords": sorted(keywords),
+        "scanned_files": [str(path) for path in scanned_files],
+        "csv": str(csv_path),
+        "video_uid_file": str(uid_path),
+    }
+    (args.out_dir / "selection_summary.json").write_text(
+        json.dumps(summary, ensure_ascii=False, indent=2),
+        encoding="utf-8",
+    )
+
+    print(json.dumps(summary, ensure_ascii=False, indent=2))
+
+
+if __name__ == "__main__":
+    main()

ego4d_selection/ego4d_selected_clips.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e17805352546c164e95fd110552463757caf51cdf99b1a81470fb207d38601f2
+size 37777634

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ego4d_selection/select_and_download_ego4d_clips.ps1

@@ -0,0 +1,47 @@
+$ErrorActionPreference = "Stop"
+
+$python = "D:\miniconda3_qwen\envs\qwen3vl_runner\python.exe"
+$ego4d = "D:\miniconda3_qwen\envs\qwen3vl_runner\Scripts\ego4d.exe"
+$root = "D:\event_driven"
+$egoRoot = "D:\ego4d_data"
+$selectionDir = "$root\01_data\ego4d_selection"
+$selector = "$selectionDir\ego4d_select_fho_tool_lta.py"
+$mapper = "$selectionDir\ego4d_map_selected_to_exported_clips.py"
+$toolDir = "$selectionDir\tool_lta_top30_fho_manifest"
+$toolCsv = "$selectionDir\tool_lta_top30\ego4d_tool_lta_selected_clips.csv"
+$uidFile = "$toolDir\ego4d_exported_clip_uids.txt"
+$env:AWS_SHARED_CREDENTIALS_FILE = "$root\secrets\aws_credentials"
+$env:AWS_CONFIG_FILE = "$root\secrets\aws_config"
+
+& $python $selector `
+  --annotations-root "$egoRoot\v2\annotations" `
+  --out-dir "$selectionDir\tool_lta_top30" `
+  --max-video-uids 30 `
+  --min-actions-per-video 1
+
+& $python $mapper `
+  --selected-csv $toolCsv `
+  --manifest-csv "$egoRoot\v2\clips\manifest.csv" `
+  --out-dir $toolDir `
+  --max-exported-clips 30
+
+if (-not (Test-Path -LiteralPath $uidFile)) {
+    throw "UID file was not created: $uidFile"
+}
+
+$uids = Get-Content -LiteralPath $uidFile | Where-Object { $_.Trim() }
+if (-not $uids) {
+    throw "No selected Ego4D video_uids. Inspect $selectionDir\ego4d_selected_clips.csv and lower --min-score if needed."
+}
+
+& $ego4d `
+  --output_directory $egoRoot `
+  --datasets clips `
+  --benchmarks FHO `
+  --aws_profile_name ego4d `
+  --video_uid_file $uidFile `
+  -y
+
+if ($LASTEXITCODE -ne 0) {
+    throw "Ego4D clips download failed. Check AWS profile/license credentials."
+}

ego4d_selection/selection_summary.json

@@ -0,0 +1,35 @@
+{
+  "annotations_root": "D:\\ego4d_data\\v2\\annotations",
+  "selected_records": 294961,
+  "selected_video_uids": 1399,
+  "min_score": 8,
+  "keywords": [
+    "board",
+    "bottle",
+    "box",
+    "cup",
+    "drill",
+    "glue",
+    "hammer",
+    "knife",
+    "nail",
+    "pliers",
+    "ruler",
+    "saw",
+    "scissors",
+    "screw",
+    "screwdriver",
+    "tape",
+    "tool",
+    "wood",
+    "wrench"
+  ],
+  "scanned_files": [
+    "D:\\ego4d_data\\v2\\annotations\\fho_oscc-pnr_train.json",
+    "D:\\ego4d_data\\v2\\annotations\\fho_oscc-pnr_val.json",
+    "D:\\ego4d_data\\v2\\annotations\\fho_sta_train.json",
+    "D:\\ego4d_data\\v2\\annotations\\fho_sta_val.json"
+  ],
+  "csv": "D:\\event_driven\\01_data\\ego4d_selection\\ego4d_selected_clips.csv",
+  "video_uid_file": "D:\\event_driven\\01_data\\ego4d_selection\\ego4d_selected_video_uids.txt"
+}

ego4d_selection/strict_tools/ego4d_selected_clips.csv

@@ -0,0 +1 @@
+source_file,score,keyword_hits,video_uid,clip_uid,annotation_uid,noun,verb

ego4d_selection/strict_tools/selection_summary.json

@@ -0,0 +1,32 @@
+{
+  "annotations_root": "D:\\ego4d_data\\v2\\annotations",
+  "selected_records": 0,
+  "selected_video_uids": 0,
+  "min_score": 12,
+  "keywords": [
+    "board",
+    "drill",
+    "glue",
+    "hammer",
+    "knife",
+    "nail",
+    "pliers",
+    "ruler",
+    "saw",
+    "scissors",
+    "screw",
+    "screwdriver",
+    "tape",
+    "tool",
+    "wood",
+    "wrench"
+  ],
+  "scanned_files": [
+    "D:\\ego4d_data\\v2\\annotations\\fho_oscc-pnr_train.json",
+    "D:\\ego4d_data\\v2\\annotations\\fho_oscc-pnr_val.json",
+    "D:\\ego4d_data\\v2\\annotations\\fho_sta_train.json",
+    "D:\\ego4d_data\\v2\\annotations\\fho_sta_val.json"
+  ],
+  "csv": "D:\\event_driven\\01_data\\ego4d_selection\\strict_tools\\ego4d_selected_clips.csv",
+  "video_uid_file": "D:\\event_driven\\01_data\\ego4d_selection\\strict_tools\\ego4d_selected_video_uids.txt"
+}

ego4d_selection/tool_lta/ego4d_tool_lta_video_uids.txt

@@ -0,0 +1,120 @@
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ego4d_selection/tool_lta/selection_summary.json

@@ -0,0 +1,251 @@
+{
+  "selected_actions": 5426,
+  "selected_video_uids": 120,
+  "max_video_uids": 120,
+  "csv": "D:\\event_driven\\01_data\\ego4d_selection\\tool_lta\\ego4d_tool_lta_selected_clips.csv",
+  "video_uid_file": "D:\\event_driven\\01_data\\ego4d_selection\\tool_lta\\ego4d_tool_lta_video_uids.txt",
+  "top_nouns": [
+    [
+      "screw_(bolt,_nail,_screw)",
+      1031
+    ],
+    [
+      "screwdriver",
+      561
+    ],
+    [
+      "wrench_(spanner,_wrench)",
+      454
+    ],
+    [
+      "tape_measure_(measure,_measurement)",
+      289
+    ],
+    [
+      "drill_(drill,_driller)",
+      265
+    ],
+    [
+      "hammer_(hammer,_mallet)",
+      259
+    ],
+    [
+      "nut_(tool)",
+      258
+    ],
+    [
+      "plier",
+      189
+    ],
+    [
+      "knife_(knife,_machete)",
+      166
+    ],
+    [
+      "scissors",
+      159
+    ],
+    [
+      "tape_(cellotape,_sellotape,_tape)",
+      157
+    ],
+    [
+      "ruler_(rule,_ruler)",
+      148
+    ],
+    [
+      "metal_(lead,_metal,_steel)",
+      115
+    ],
+    [
+      "wood_(fiber,_firewood,_floorboard,_log,_lumber,_plank,_plywood,_timber,_wood,_woodcraft,_woodwork)",
+      109
+    ],
+    [
+      "nail_gun",
+      102
+    ],
+    [
+      "rod_(dipstick,_rod,_rod_metal,_shaft)",
+      84
+    ],
+    [
+      "saw_(chainsaw,_saw,_hacksaw)",
+      78
+    ],
+    [
+      "cutter_(tool)",
+      77
+    ],
+    [
+      "awl",
+      77
+    ],
+    [
+      "drill_bit",
+      64
+    ],
+    [
+      "glue_(adhesive,_glue,_gum,_sealant)",
+      63
+    ],
+    [
+      "set_square_(tool)",
+      60
+    ],
+    [
+      "file_(tool)",
+      43
+    ],
+    [
+      "ladder",
+      41
+    ],
+    [
+      "toolbox",
+      38
+    ],
+    [
+      "caliper",
+      35
+    ],
+    [
+      "engine_(assembly,_carburetor,_engine,_motor)",
+      32
+    ],
+    [
+      "wheel_(tyre,_wheel)",
+      30
+    ],
+    [
+      "iron",
+      30
+    ],
+    [
+      "bolt_extractor",
+      26
+    ]
+  ],
+  "top_verbs": [
+    [
+      "take_(pick,_grab,_get)",
+      1373
+    ],
+    [
+      "put_(place,_leave,_drop)",
+      1308
+    ],
+    [
+      "hit_(knock,_hit,_hammer)",
+      247
+    ],
+    [
+      "hold_(support,_grip,_grasp)",
+      240
+    ],
+    [
+      "move_(transfer,_pass,_exchange)",
+      239
+    ],
+    [
+      "remove",
+      183
+    ],
+    [
+      "tighten",
+      170
+    ],
+    [
+      "measure_(weigh,_measure)",
+      160
+    ],
+    [
+      "weld",
+      123
+    ],
+    [
+      "attach_(plug-in,_join,_fasten,_connect,_attach)",
+      117
+    ],
+    [
+      "screw",
+      110
+    ],
+    [
+      "repair",
+      104
+    ],
+    [
+      "drill",
+      102
+    ],
+    [
+      "loosen",
+      101
+    ],
+    [
+      "insert",
+      99
+    ],
+    [
+      "adjust_(regulate,_increase/reduce,_change)",
+      69
+    ],
+    [
+      "touch",
+      59
+    ],
+    [
+      "pull",
+      59
+    ],
+    [
+      "open",
+      50
+    ],
+    [
+      "unscrew",
+      41
+    ],
+    [
+      "apply_(spread,_smear)",
+      29
+    ],
+    [
+      "turn_(spin,_rotate,_flip,_turn_over)",
+      29
+    ],
+    [
+      "push",
+      27
+    ],
+    [
+      "operate_(use,_dial,_click-button)",
+      24
+    ],
+    [
+      "carry",
+      24
+    ],
+    [
+      "clean_(sweep,_scrub,_mop,_dust)",
+      24
+    ],
+    [
+      "close",
+      20
+    ],
+    [
+      "drive_(ride,_drive)",
+      19
+    ],
+    [
+      "hang",
+      19
+    ],
+    [
+      "throw_(toss,_dump,_dispose)",
+      18
+    ]
+  ]
+}

ego4d_selection/tool_lta_top30/downloadable_clip_summary.json

@@ -0,0 +1,9 @@
+{
+  "selected_annotation_rows": 2379,
+  "selected_clip_uids": 115,
+  "selected_video_uids": 30,
+  "matched_exported_clips": 30,
+  "max_exported_clips": 30,
+  "uid_file": "D:\\event_driven\\01_data\\ego4d_selection\\tool_lta_top30\\ego4d_exported_clip_uids.txt",
+  "csv": "D:\\event_driven\\01_data\\ego4d_selection\\tool_lta_top30\\ego4d_downloadable_exported_clips.csv"
+}

ego4d_selection/tool_lta_top30/ego4d_downloadable_exported_clips.csv

@@ -0,0 +1,31 @@
+exported_clip_uid,parent_video_uid,parent_clip_uid,parent_start_sec,parent_end_sec,parent_frame_start,parent_frame_end,exported_timestamp,s3_path,manifold_location,type,file_uid,benchmarks
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+03b29198-6447-46b7-aa69-aff7a2b01a5b,1e5bd816-e1dd-43d3-8709-42c83114dc7c,,592.0,908.0,17759,27239,1672962959,s3://ego4d-iiith/public/v2/clips/03b29198-6447-46b7-aa69-aff7a2b01a5b.mp4,manifold://ego4d_fair/tree/exported_clips/03b29198-6447-46b7-aa69-aff7a2b01a5b.mp4,file,03b29198-6447-46b7-aa69-aff7a2b01a5b,[FHO]
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ego4d_selection/tool_lta_top30/ego4d_exported_clip_uids.txt

@@ -0,0 +1,30 @@
+004e8f11-9d56-4208-aeaf-77b03ced000c
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+1953891d-6925-44b7-893c-27e1fa3c3696

ego4d_selection/tool_lta_top30/ego4d_tool_lta_video_uids.txt

@@ -0,0 +1,30 @@
+1e5bd816-e1dd-43d3-8709-42c83114dc7c
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+dabcf717-b9f8-4547-b395-2745e2a45356

ego4d_selection/tool_lta_top30/selection_summary.json

@@ -0,0 +1,251 @@
+{
+  "selected_actions": 2379,
+  "selected_video_uids": 30,
+  "max_video_uids": 30,
+  "csv": "D:\\event_driven\\01_data\\ego4d_selection\\tool_lta_top30\\ego4d_tool_lta_selected_clips.csv",
+  "video_uid_file": "D:\\event_driven\\01_data\\ego4d_selection\\tool_lta_top30\\ego4d_tool_lta_video_uids.txt",
+  "top_nouns": [
+    [
+      "screw_(bolt,_nail,_screw)",
+      388
+    ],
+    [
+      "screwdriver",
+      214
+    ],
+    [
+      "tape_measure_(measure,_measurement)",
+      166
+    ],
+    [
+      "hammer_(hammer,_mallet)",
+      164
+    ],
+    [
+      "drill_(drill,_driller)",
+      138
+    ],
+    [
+      "wrench_(spanner,_wrench)",
+      116
+    ],
+    [
+      "nut_(tool)",
+      107
+    ],
+    [
+      "knife_(knife,_machete)",
+      100
+    ],
+    [
+      "scissors",
+      92
+    ],
+    [
+      "ruler_(rule,_ruler)",
+      86
+    ],
+    [
+      "awl",
+      77
+    ],
+    [
+      "wood_(fiber,_firewood,_floorboard,_log,_lumber,_plank,_plywood,_timber,_wood,_woodcraft,_woodwork)",
+      65
+    ],
+    [
+      "tape_(cellotape,_sellotape,_tape)",
+      56
+    ],
+    [
+      "metal_(lead,_metal,_steel)",
+      56
+    ],
+    [
+      "glue_(adhesive,_glue,_gum,_sealant)",
+      54
+    ],
+    [
+      "plier",
+      47
+    ],
+    [
+      "rod_(dipstick,_rod,_rod_metal,_shaft)",
+      46
+    ],
+    [
+      "drill_bit",
+      44
+    ],
+    [
+      "ladder",
+      41
+    ],
+    [
+      "cutter_(tool)",
+      39
+    ],
+    [
+      "iron",
+      29
+    ],
+    [
+      "saw_(chainsaw,_saw,_hacksaw)",
+      22
+    ],
+    [
+      "set_square_(tool)",
+      20
+    ],
+    [
+      "chisel",
+      17
+    ],
+    [
+      "engine_(assembly,_carburetor,_engine,_motor)",
+      17
+    ],
+    [
+      "stool",
+      15
+    ],
+    [
+      "bolt_extractor",
+      14
+    ],
+    [
+      "table_(stand,_table)",
+      13
+    ],
+    [
+      "nail_gun",
+      12
+    ],
+    [
+      "toolbox",
+      9
+    ]
+  ],
+  "top_verbs": [
+    [
+      "take_(pick,_grab,_get)",
+      571
+    ],
+    [
+      "put_(place,_leave,_drop)",
+      556
+    ],
+    [
+      "hold_(support,_grip,_grasp)",
+      131
+    ],
+    [
+      "hit_(knock,_hit,_hammer)",
+      112
+    ],
+    [
+      "measure_(weigh,_measure)",
+      100
+    ],
+    [
+      "move_(transfer,_pass,_exchange)",
+      89
+    ],
+    [
+      "remove",
+      84
+    ],
+    [
+      "weld",
+      75
+    ],
+    [
+      "tighten",
+      74
+    ],
+    [
+      "insert",
+      68
+    ],
+    [
+      "repair",
+      50
+    ],
+    [
+      "loosen",
+      44
+    ],
+    [
+      "adjust_(regulate,_increase/reduce,_change)",
+      44
+    ],
+    [
+      "attach_(plug-in,_join,_fasten,_connect,_attach)",
+      42
+    ],
+    [
+      "drill",
+      35
+    ],
+    [
+      "open",
+      30
+    ],
+    [
+      "pull",
+      30
+    ],
+    [
+      "touch",
+      26
+    ],
+    [
+      "screw",
+      25
+    ],
+    [
+      "push",
+      22
+    ],
+    [
+      "roll",
+      16
+    ],
+    [
+      "apply_(spread,_smear)",
+      13
+    ],
+    [
+      "press",
+      11
+    ],
+    [
+      "drive_(ride,_drive)",
+      11
+    ],
+    [
+      "throw_(toss,_dump,_dispose)",
+      9
+    ],
+    [
+      "turn_(spin,_rotate,_flip,_turn_over)",
+      9
+    ],
+    [
+      "close",
+      8
+    ],
+    [
+      "clean_(sweep,_scrub,_mop,_dust)",
+      8
+    ],
+    [
+      "lift",
+      8
+    ],
+    [
+      "hang",
+      7
+    ]
+  ]
+}

ego4d_selection/tool_lta_top30_fho_manifest/downloadable_clip_summary.json

@@ -0,0 +1,9 @@
+{
+  "selected_annotation_rows": 2379,
+  "selected_clip_uids": 115,
+  "selected_video_uids": 30,
+  "matched_exported_clips": 30,
+  "max_exported_clips": 30,
+  "uid_file": "D:\\event_driven\\01_data\\ego4d_selection\\tool_lta_top30_fho_manifest\\ego4d_exported_clip_uids.txt",
+  "csv": "D:\\event_driven\\01_data\\ego4d_selection\\tool_lta_top30_fho_manifest\\ego4d_downloadable_exported_clips.csv"
+}

ego4d_selection/tool_lta_top30_fho_manifest/ego4d_downloadable_exported_clips.csv

@@ -0,0 +1,31 @@
+exported_clip_uid,parent_video_uid,parent_clip_uid,parent_start_sec,parent_end_sec,parent_frame_start,parent_frame_end,exported_timestamp,s3_path,manifold_location,type,file_uid,benchmarks
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ego4d_selection/tool_lta_top30_fho_manifest/ego4d_exported_clip_uids.txt

@@ -0,0 +1,30 @@
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