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"#Multi GPU Usage code (with fade in/out on final video)\n",
"# === DEBUG: List all mounted Kaggle datasets ===\n",
"import os as _dbg_os\n",
"print(\"=== Mounted Kaggle Datasets ===\")\n",
"for _dbg_d in sorted(_dbg_os.listdir(\"/kaggle/input/\")):\n",
" _dbg_p = _dbg_os.path.join(\"/kaggle/input/\", _dbg_d)\n",
" if _dbg_os.path.isdir(_dbg_p):\n",
" _dbg_files = _dbg_os.listdir(_dbg_p)\n",
" print(f\" /kaggle/input/{_dbg_d}/ ({len(_dbg_files)} files)\")\n",
" for _dbg_f in sorted(_dbg_files):\n",
" print(f\" {_dbg_f}\")\n",
"print(\"=\" * 40)\n",
"# === END DEBUG ===\n",
"import subprocess, os, sys, re, threading, time, json\n",
"\n",
"def load_crop_resize_from_config(config_path):\n",
" \"\"\"\n",
" Reads crop_config.json (as produced by preview_cropper.py) and converts:\n",
" - computed_crop_region -> decoder -crop (top x bottom x left x right)\n",
" - cover_zoom_transform -> decoder -resize (zoomed WxH) PLUS the\n",
" centered offset needed to crop that\n",
" zoomed frame back down to the ORIGINAL\n",
" (final) width x height.\n",
" Returns None if no config_path given, or if file doesn't exist.\n",
" \"\"\"\n",
" if not config_path or not os.path.exists(config_path):\n",
" return None\n",
"\n",
" with open(config_path, \"r\") as f:\n",
" cfg = json.load(f)\n",
"\n",
" meta = cfg[\"video_metadata\"]\n",
" src_w, src_h = meta[\"width\"], meta[\"height\"]\n",
"\n",
" region = cfg[\"computed_crop_region\"]\n",
" x1, y1, x2, y2 = region[\"x1\"], region[\"y1\"], region[\"x2\"], region[\"y2\"]\n",
"\n",
" crop_top = y1\n",
" crop_bottom = src_h - y2\n",
" crop_left = x1\n",
" crop_right = src_w - x2\n",
"\n",
" zoom = cfg[\"cover_zoom_transform\"]\n",
" resize_w = zoom[\"zoomed_width\"]\n",
" resize_h = zoom[\"zoomed_height\"]\n",
" center_offset_x = zoom.get(\"center_offset_x\", 0)\n",
" center_offset_y = zoom.get(\"center_offset_y\", 0)\n",
"\n",
" print(\"🧩 Loaded crop/resize from config.json:\")\n",
" print(f\" Source resolution: {src_w}x{src_h}\")\n",
" print(f\" Crop region: x1={x1} y1={y1} x2={x2} y2={y2}\")\n",
" print(f\" -> decoder crop (top:bottom:left:right) = {crop_top}x{crop_bottom}x{crop_left}x{crop_right}\")\n",
" print(f\" -> decoder resize (zoomed/cover) target = {resize_w}x{resize_h}\")\n",
" print(f\" -> final center-crop back to {src_w}x{src_h} at offset ({center_offset_x}, {center_offset_y})\")\n",
"\n",
" return {\n",
" \"crop_top\": crop_top,\n",
" \"crop_bottom\": crop_bottom,\n",
" \"crop_left\": crop_left,\n",
" \"crop_right\": crop_right,\n",
" \"resize_w\": resize_w,\n",
" \"resize_h\": resize_h,\n",
" \"center_offset_x\": center_offset_x,\n",
" \"center_offset_y\": center_offset_y,\n",
" \"final_width\": src_w,\n",
" \"final_height\": src_h,\n",
" \"filename\": cfg.get(\"filename\"),\n",
" \"task_id\": cfg.get(\"task_id\"),\n",
" }\n",
"\n",
"# Map ffprobe codec_name -> matching CUVID decoder\n",
"CUVID_MAP = {\n",
" \"h264\": \"h264_cuvid\",\n",
" \"hevc\": \"hevc_cuvid\",\n",
" \"vp9\": \"vp9_cuvid\",\n",
" \"vp8\": \"vp8_cuvid\",\n",
" \"mpeg2video\": \"mpeg2_cuvid\",\n",
" \"mpeg4\": \"mpeg4_cuvid\",\n",
" \"vc1\": \"vc1_cuvid\",\n",
" \"av1\": \"av1_cuvid\",\n",
"}\n",
"\n",
"# Decoders that support the cuvid -crop / -resize options.\n",
"CROP_RESIZE_CAPABLE_DECODERS = {\"h264_cuvid\", \"hevc_cuvid\", \"vp9_cuvid\"}\n",
"\n",
"def detect_codec(path):\n",
" out = subprocess.run(\n",
" [\"ffprobe\", \"-v\", \"error\", \"-select_streams\", \"v:0\",\n",
" \"-show_entries\", \"stream=codec_name\", \"-of\", \"csv=p=0\", path],\n",
" stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True\n",
" )\n",
" codec = out.stdout.strip()\n",
" if not codec:\n",
" raise RuntimeError(f\"Could not detect codec. ffprobe stderr: {out.stderr}\")\n",
" return codec\n",
"\n",
"def get_duration_seconds(path):\n",
" out = subprocess.run(\n",
" [\"ffprobe\", \"-v\", \"error\", \"-show_entries\", \"format=duration\",\n",
" \"-of\", \"csv=p=0\", path],\n",
" stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True\n",
" )\n",
" dur_str = out.stdout.strip()\n",
" if not dur_str:\n",
" raise RuntimeError(f\"Could not detect duration. ffprobe stderr: {out.stderr}\")\n",
" return float(dur_str)\n",
"\n",
"def check_gpus():\n",
" out = subprocess.run([\"nvidia-smi\", \"-L\"], stdout=subprocess.PIPE, text=True)\n",
" print(out.stdout.strip())\n",
" n = out.stdout.strip().count(\"GPU \")\n",
" if n < 2:\n",
" print(\"⚠️ Less than 2 GPUs detected — both jobs (if split) will run concurrently on GPU0.\")\n",
" return n\n",
"\n",
"PROGRESS_RE = re.compile(\n",
" r\"frame=\\s*(\\d+).*fps=\\s*([\\d.]+).*time=(\\S+).*?(?:dup=(\\d+))?.*?(?:drop=(\\d+))?.*speed=\\s*([\\d.]+)x\"\n",
")\n",
"\n",
"shared_state = {\"GPU0\": \"starting...\", \"GPU1\": \"starting...\"}\n",
"state_lock = threading.Lock()\n",
"\n",
"def render_combined_line():\n",
" line = f\"\\r[GPU0] {shared_state['GPU0']} || [GPU1] {shared_state['GPU1']}\"\n",
" sys.stdout.write(line.ljust(180))\n",
" sys.stdout.flush()\n",
"\n",
"def stream_progress(proc, tag, log_lines):\n",
" \"\"\"Read ffmpeg stderr line/chunk-wise (not char-by-char) to avoid pipe backpressure\n",
" that can stall the encoder itself while waiting on Python to drain stderr.\"\"\"\n",
" buf = \"\"\n",
" while True:\n",
" chunk = proc.stderr.read(4096)\n",
" if not chunk:\n",
" break\n",
" buf += chunk\n",
" while True:\n",
" idx_r = buf.find(\"\\r\")\n",
" idx_n = buf.find(\"\\n\")\n",
" idx = min([i for i in (idx_r, idx_n) if i != -1], default=-1)\n",
" if idx == -1:\n",
" break\n",
" line = buf[:idx].strip()\n",
" buf = buf[idx+1:]\n",
" if line:\n",
" log_lines.append(line)\n",
" m = PROGRESS_RE.search(line)\n",
" if m:\n",
" frame, fps, t, dup, drop, speed = m.groups()\n",
" dup = dup or \"0\"\n",
" drop = drop or \"0\"\n",
" flag = \" ⚠️DROP!\" if int(drop) > 0 else \"\"\n",
" with state_lock:\n",
" shared_state[tag] = f\"frame={frame} fps={fps} time={t} dup={dup} drop={drop}{flag} speed={speed}x\"\n",
" render_combined_line()\n",
" if buf.strip():\n",
" log_lines.append(buf.strip())\n",
"\n",
"def run_with_progress(cmd, tag):\n",
" print(f\"\\n▶️ Starting {tag}: {' '.join(cmd)}\\n\")\n",
" p = subprocess.Popen(cmd, stdout=subprocess.DEVNULL, stderr=subprocess.PIPE, text=True, bufsize=1)\n",
" log_lines = []\n",
" t = threading.Thread(target=stream_progress, args=(p, tag, log_lines))\n",
" t.start()\n",
" return p, t, log_lines\n",
"\n",
"# Preset is fixed to p3 (better quality) for all encode jobs, regardless of GPU count.\n",
"PRESET = \"p3\"\n",
"\n",
"# Bitrate ceiling to prevent -cq from ballooning file size on complex/high-motion scenes.\n",
"MAXRATE = \"30M\"\n",
"BUFSIZE = \"60M\"\n",
"\n",
"# If video is longer than this, split into 2 parts and process in parallel.\n",
"# If video is this length or shorter, process as a single job (no split).\n",
"SPLIT_THRESHOLD_SEC = 25 * 60 # 25 minutes\n",
"\n",
"# ---------------- Fade in/out config (applied to the FINAL video only) ----------------\n",
"FADE_DURATION_SEC = 1.5 # length of each fade, in seconds. Bump to 2.0 for a more noticeable fade.\n",
"\n",
"# ---------------- Intro / Outro config ----------------\n",
"# If BOTH files exist, they are stitched onto the final video using a fast\n",
"# stream-copy concat (-c copy) — no re-encode, near-zero extra time.\n",
"# In that case, fade-in/out is SKIPPED (intro/outro replaces the need for it).\n",
"# If either file is missing, we fall back to fade-in/out as before.\n",
"INTRO_PATH = \"/kaggle/input/datasets/joymant/intro-outro/intro.mp4\"\n",
"OUTRO_PATH = \"/kaggle/input/datasets/joymant/intro-outro/outro.mp4\"\n",
"# NOTE: MAIN_ONLY_PATH and INTRO_OUTRO_LIST_PATH are defined further below,\n",
"# right after TEMP_DIR is created.\n",
"\n",
"\n",
"def has_intro_outro():\n",
" found = os.path.exists(INTRO_PATH) and os.path.exists(OUTRO_PATH)\n",
" if found:\n",
" print(f\"🎬 Intro + Outro detected:\\n intro: {INTRO_PATH}\\n outro: {OUTRO_PATH}\")\n",
" print(\" -> Will stitch via fast stream-copy concat (-c copy). Fade-in/out will be SKIPPED.\")\n",
" else:\n",
" print(\"🎬 Intro/Outro not found (one or both missing) -> falling back to fade-in/out.\")\n",
" return found\n",
"\n",
"\n",
"def stitch_intro_outro(main_video_path, final_output_path):\n",
" \"\"\"\n",
" Fast, copy-only concat: intro.mp4 + main_video_path + outro.mp4 -> final_output_path.\n",
" No re-encoding happens here, so this adds negligible time regardless of video length.\n",
" NOTE: for stream-copy concat to work cleanly, intro/outro should already match the\n",
" main video's codec/resolution/fps/pixel format. If they don't, ffmpeg's concat demuxer\n",
" may still produce a playable file, but mismatches won't be auto-corrected since we're\n",
" deliberately avoiding re-encode here for speed.\n",
" \"\"\"\n",
" print(\"🔗 Stitching intro + main + outro (stream copy, no re-encode)...\")\n",
" with open(INTRO_OUTRO_LIST_PATH, \"w\") as f:\n",
" f.write(f\"file '{INTRO_PATH}'\\nfile '{main_video_path}'\\nfile '{OUTRO_PATH}'\")\n",
"\n",
" concat_cmd = [\"ffmpeg\", \"-y\", \"-f\", \"concat\", \"-safe\", \"0\", \"-i\", INTRO_OUTRO_LIST_PATH,\n",
" \"-c\", \"copy\", final_output_path]\n",
" res = subprocess.run(concat_cmd, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, text=True)\n",
" if res.returncode != 0:\n",
" print(res.stdout)\n",
" raise RuntimeError(\"intro/outro stitch failed — check that intro/outro codec/resolution/fps \"\n",
" \"match the main video (stream copy requires matching parameters).\")\n",
"\n",
" for f in (MAIN_ONLY_PATH, INTRO_OUTRO_LIST_PATH):\n",
" if os.path.exists(f):\n",
" os.remove(f)\n",
" print(\"✅ Intro/outro stitched successfully (fast copy, no quality loss, no re-encode time).\")\n",
"\n",
"# Kaggle directories:\n",
"# /kaggle/working -> downloaded by `kaggle kernels output` (KEEP ONLY FINAL FILE HERE)\n",
"# /kaggle/temp -> NOT downloaded by kernels output, safe for intermediates (part1.mp4, part2.mp4, list.txt)\n",
"WORKING_DIR = \"/kaggle/working\"\n",
"TEMP_DIR = \"/kaggle/temp\"\n",
"\n",
"os.makedirs(WORKING_DIR, exist_ok=True)\n",
"os.makedirs(TEMP_DIR, exist_ok=True)\n",
"\n",
"FINAL_OUTPUT_PATH = os.path.join(WORKING_DIR, \"final_output_4k.mp4\")\n",
"PART1_PATH = os.path.join(TEMP_DIR, \"part1.mp4\")\n",
"PART2_PATH = os.path.join(TEMP_DIR, \"part2.mp4\")\n",
"LIST_TXT_PATH = os.path.join(TEMP_DIR, \"list.txt\")\n",
"MAIN_ONLY_PATH = os.path.join(TEMP_DIR, \"main_only.mp4\")\n",
"INTRO_OUTRO_LIST_PATH = os.path.join(TEMP_DIR, \"intro_outro_list.txt\")\n",
"\n",
"# ---------------- Logo overlay config ----------------\n",
"LOGO_LEFT_PATH = \"/kaggle/input/datasets/joymant/logo-datasets/logo1.png\"\n",
"LOGO_RIGHT_PATH = \"/kaggle/input/datasets/joymant/logo-datasets/logo2.png\"\n",
"\n",
"# Reference geometry measured on a 1920x1080 (1080p) canvas:\n",
"REF_WIDTH = 1920\n",
"REF_LOGO_SIZE = 137 # logo box is 137x137 at 1080p\n",
"REF_MARGIN_LEFT = 22 # left logo: distance from left edge\n",
"REF_MARGIN_TOP = 18 # both logos: distance from top edge\n",
"REF_MARGIN_RIGHT = 22 # right logo: distance from right edge (mirrors left margin)\n",
"\n",
"\n",
"def get_video_resolution(path):\n",
" out = subprocess.run(\n",
" [\"ffprobe\", \"-v\", \"error\", \"-select_streams\", \"v:0\",\n",
" \"-show_entries\", \"stream=width,height\", \"-of\", \"csv=p=0:s=x\", path],\n",
" stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True\n",
" )\n",
" res = out.stdout.strip()\n",
" if not res or \"x\" not in res:\n",
" raise RuntimeError(f\"Could not detect resolution. ffprobe stderr: {out.stderr}\")\n",
" w, h = res.split(\"x\")\n",
" return int(w), int(h)\n",
"\n",
"\n",
"def compute_logo_geometry(target_w, target_h):\n",
" \"\"\"\n",
" Scales the reference 1080p logo geometry to any output resolution,\n",
" keeping it proportional (based on width ratio vs the 1920px reference).\n",
" Returns dict with logo size + x/y positions for both logos, all even numbers\n",
" (required by some encoders/filters for clean scaling).\n",
" \"\"\"\n",
" scale = target_w / REF_WIDTH\n",
"\n",
" def even(n):\n",
" n = int(round(n))\n",
" return n - (n % 2)\n",
"\n",
" logo_size = even(REF_LOGO_SIZE * scale)\n",
" margin_left = even(REF_MARGIN_LEFT * scale)\n",
" margin_top = even(REF_MARGIN_TOP * scale)\n",
" margin_right = even(REF_MARGIN_RIGHT * scale)\n",
"\n",
" left_x = margin_left\n",
" left_y = margin_top\n",
" right_x = target_w - margin_right - logo_size\n",
" right_y = margin_top\n",
"\n",
" print(f\"🖼️ Logo geometry for {target_w}x{target_h} (scale={scale:.3f}):\")\n",
" print(f\" logo size: {logo_size}x{logo_size}\")\n",
" print(f\" left logo position : x={left_x} y={left_y}\")\n",
" print(f\" right logo position: x={right_x} y={right_y}\")\n",
"\n",
" return {\n",
" \"size\": logo_size,\n",
" \"left_x\": left_x, \"left_y\": left_y,\n",
" \"right_x\": right_x, \"right_y\": right_y,\n",
" }\n",
"\n",
"\n",
"def build_logo_filter_complex(geo, base_video_label=\"0:v\",\n",
" fade_in=False, fade_out_start=None,\n",
" fade_dur=FADE_DURATION_SEC,\n",
" final_crop=None):\n",
" \"\"\"\n",
" Builds the -filter_complex string + extra ffmpeg input args needed to\n",
" overlay both logos on a CUDA-decoded video, optionally apply fade-in/out,\n",
" then re-upload to CUDA for NVENC.\n",
"\n",
" fade_in : True -> add a fade-in starting at t=0\n",
" fade_out_start : float seconds (relative to THIS job's own clip, not the\n",
" original full video) -> add a fade-out starting there.\n",
" None -> no fade-out on this job.\n",
" fade_dur : duration of each fade in seconds.\n",
" final_crop : optional dict {\"w\", \"h\", \"x\", \"y\"}. When the decoder's\n",
" -resize produced a \"cover zoom\" frame that's LARGER than\n",
" the true final canvas (e.g. 1920x1252 zoomed vs the real\n",
" 1920x1080 target), this crops it back down to w x h at\n",
" the centered offset (x, y) BEFORE logos are overlaid, so\n",
" logo placement and final resolution both land on the\n",
" real target canvas instead of the intermediate zoom size.\n",
"\n",
" Returns (extra_input_args, filter_complex_str, output_video_label)\n",
" \"\"\"\n",
" size = geo[\"size\"]\n",
" extra_inputs = [\"-i\", LOGO_LEFT_PATH, \"-i\", LOGO_RIGHT_PATH]\n",
"\n",
" fade_str = \"\"\n",
" if fade_in:\n",
" fade_str += f\"fade=t=in:st=0:d={fade_dur},\"\n",
" if fade_out_start is not None:\n",
" fade_str += f\"fade=t=out:st={max(0, fade_out_start)}:d={fade_dur},\"\n",
"\n",
" crop_part = \"\"\n",
" if final_crop:\n",
" crop_part = f\",crop={final_crop['w']}:{final_crop['h']}:{final_crop['x']}:{final_crop['y']}\"\n",
"\n",
" filter_complex = (\n",
" f\"[{base_video_label}]hwdownload,format=nv12{crop_part}[mainsw];\"\n",
" f\"[1:v]scale={size}:{size}[logoL];\"\n",
" f\"[2:v]scale={size}:{size}[logoR];\"\n",
" f\"[mainsw][logoL]overlay=x={geo['left_x']}:y={geo['left_y']}[tmp1];\"\n",
" f\"[tmp1][logoR]overlay=x={geo['right_x']}:y={geo['right_y']}[tmp2];\"\n",
" f\"[tmp2]{fade_str}hwupload_cuda[vout]\"\n",
" )\n",
" return extra_inputs, filter_complex, \"[vout]\"\n",
"\n",
"\n",
"def parallel_dual_gpu_safe(config_path=None, input_video_override=None):\n",
" overall_start = time.time()\n",
" input_video = \"/kaggle/input/20260629-172948-b2177c/output_20260629_172948_b2177c.mkv\"\n",
"\n",
" n_gpus = check_gpus()\n",
"\n",
" # ---- Decide intro/outro vs fade-in/out up front ----\n",
" use_intro_outro = has_intro_outro()\n",
" use_fade = not use_intro_outro\n",
"\n",
" # ---- Optional crop/resize from config.json (decoder-level GPU crop+resize) ----\n",
" crop_resize = load_crop_resize_from_config(config_path)\n",
" crop_resize_args = []\n",
" final_crop = None # set below if the decoder's cover-zoom overshoots the real canvas\n",
" if crop_resize:\n",
" ct, cb, cl, cr = (crop_resize[\"crop_top\"], crop_resize[\"crop_bottom\"],\n",
" crop_resize[\"crop_left\"], crop_resize[\"crop_right\"])\n",
" if ct or cb or cl or cr:\n",
" crop_resize_args += [\"-crop\", f\"{ct}x{cb}x{cl}x{cr}\"]\n",
" if crop_resize[\"resize_w\"] and crop_resize[\"resize_h\"]:\n",
" rw = crop_resize[\"resize_w\"] - (crop_resize[\"resize_w\"] % 2)\n",
" rh = crop_resize[\"resize_h\"] - (crop_resize[\"resize_h\"] % 2)\n",
" if (rw, rh) != (crop_resize[\"resize_w\"], crop_resize[\"resize_h\"]):\n",
" print(f\"⚠️ Resize target {crop_resize['resize_w']}x{crop_resize['resize_h']} has odd dimension(s) \"\n",
" f\"(NVENC requires even) — rounding down to {rw}x{rh}\")\n",
" crop_resize_args += [\"-resize\", f\"{rw}x{rh}\"]\n",
"\n",
" fw, fh = crop_resize[\"final_width\"], crop_resize[\"final_height\"]\n",
" if (rw, rh) != (fw, fh):\n",
" final_crop = {\n",
" \"w\": fw, \"h\": fh,\n",
" \"x\": crop_resize[\"center_offset_x\"],\n",
" \"y\": crop_resize[\"center_offset_y\"],\n",
" }\n",
" print(f\"✂️ Decoder resize ({rw}x{rh}) overshoots the final canvas ({fw}x{fh}) — \"\n",
" f\"will center-crop back to {fw}x{fh} at offset \"\n",
" f\"({final_crop['x']}, {final_crop['y']}) before overlaying logos.\")\n",
"\n",
" if input_video_override:\n",
" input_video = input_video_override\n",
" print(f\"📁 Using EXPLICIT input override (ignoring config's filename): {input_video}\")\n",
" elif crop_resize.get(\"filename\"):\n",
" candidate = os.path.join(os.path.dirname(config_path), crop_resize[\"filename\"])\n",
" if os.path.exists(candidate):\n",
" input_video = candidate\n",
" print(f\"📁 Using input from config: {input_video}\")\n",
" elif input_video_override:\n",
" input_video = input_video_override\n",
" print(f\"📁 Using EXPLICIT input override: {input_video}\")\n",
"\n",
" codec = detect_codec(input_video)\n",
" decoder = CUVID_MAP.get(codec)\n",
" if decoder is None:\n",
" raise RuntimeError(f\"No CUVID decoder mapping for detected codec '{codec}'. \"\n",
" f\"Known: {list(CUVID_MAP)}\")\n",
" print(f\"🎯 Detected input codec: {codec} -> using decoder: {decoder}\")\n",
"\n",
" if crop_resize_args and decoder not in CROP_RESIZE_CAPABLE_DECODERS:\n",
" print(f\"⚠️ -crop/-resize decoder options are only supported for {sorted(CROP_RESIZE_CAPABLE_DECODERS)}. \"\n",
" f\"Detected decoder '{decoder}' — crop/resize will be SKIPPED.\")\n",
" crop_resize_args = []\n",
" final_crop = None\n",
"\n",
" duration = get_duration_seconds(input_video)\n",
" print(f\"🕒 Video duration: {duration/60:.2f} min\")\n",
"\n",
" # ---- Determine actual FINAL output resolution for logo scaling ----\n",
" # This must be the true final canvas (post center-crop-back), not the\n",
" # intermediate \"cover zoom\" resize size, otherwise logos get placed\n",
" # relative to a frame that no longer exists in the output.\n",
" if crop_resize and crop_resize.get(\"final_width\") and crop_resize.get(\"final_height\"):\n",
" target_w, target_h = crop_resize[\"final_width\"], crop_resize[\"final_height\"]\n",
" else:\n",
" target_w, target_h = get_video_resolution(input_video)\n",
" logo_geo = compute_logo_geometry(target_w, target_h)\n",
"\n",
" # ---- Case A: short video — single job, no split ----\n",
" if duration <= SPLIT_THRESHOLD_SEC:\n",
" print(f\"📦 Video ≤ {SPLIT_THRESHOLD_SEC/60:.0f} min — processing as a SINGLE job (no split) on GPU0\")\n",
" encode_target = MAIN_ONLY_PATH if use_intro_outro else FINAL_OUTPUT_PATH\n",
" if use_fade:\n",
" print(f\"🎬 Applying fade-in at t=0 and fade-out at t={max(0, duration - FADE_DURATION_SEC):.2f}s \"\n",
" f\"(duration={FADE_DURATION_SEC}s each)\")\n",
" extra_inputs, filter_complex, vlabel = build_logo_filter_complex(\n",
" logo_geo, \"0:v\",\n",
" fade_in=use_fade,\n",
" fade_out_start=(duration - FADE_DURATION_SEC) if use_fade else None,\n",
" final_crop=final_crop,\n",
" )\n",
" cmd = [\n",
" \"ffmpeg\", \"-y\",\n",
" \"-hwaccel\", \"cuda\", \"-hwaccel_device\", \"0\", \"-hwaccel_output_format\", \"cuda\",\n",
" \"-c:v\", decoder,\n",
" ] + crop_resize_args + [\n",
" \"-i\", input_video,\n",
" ] + extra_inputs + [\n",
" \"-filter_complex\", filter_complex,\n",
" \"-map\", vlabel, \"-map\", \"0:a?\",\n",
" \"-c:v\", \"hevc_nvenc\", \"-gpu\", \"0\", \"-preset\", PRESET, \"-cq\", \"18\",\n",
" \"-maxrate\", MAXRATE, \"-bufsize\", BUFSIZE,\n",
" \"-c:a\", \"copy\",\n",
" encode_target\n",
" ]\n",
" start_time = time.time()\n",
" p, t, log = run_with_progress(cmd, \"GPU0\")\n",
" p.wait(); t.join()\n",
" print()\n",
" if p.returncode != 0:\n",
" print(\"\\n\".join(log[-15:]))\n",
" raise RuntimeError(\"single job failed\")\n",
" elapsed = time.time() - start_time\n",
" print(f\"\\n⏱️ Job finished in {elapsed/60:.2f} min ({elapsed:.1f} sec)\")\n",
"\n",
" if use_intro_outro:\n",
" stitch_intro_outro(MAIN_ONLY_PATH, FINAL_OUTPUT_PATH)\n",
"\n",
" print(f\"📦 Final video saved at: {FINAL_OUTPUT_PATH}\")\n",
" total_elapsed = time.time() - overall_start\n",
" print(f\"🏁 TOTAL TIME TAKEN: {total_elapsed/60:.2f} min ({total_elapsed:.1f} sec)\")\n",
" return\n",
"\n",
" # ---- Case B: long video (> 25 min) — split into 2 parts at the exact midpoint ----\n",
" split_seconds = duration / 2\n",
" split_point = time.strftime(\"%H:%M:%S\", time.gmtime(split_seconds))\n",
" print(f\"✂️ Video > {SPLIT_THRESHOLD_SEC/60:.0f} min — splitting at exact midpoint: {split_point} \"\n",
" f\"(frame-accurate, GPU re-encode)\")\n",
"\n",
" # part2's own (independent) duration, needed to place its fade-out correctly\n",
" part2_duration = duration - split_seconds\n",
" if use_fade:\n",
" print(f\"🎬 Fade-in (t=0) will be applied to part1 only. \"\n",
" f\"Fade-out (t={max(0, part2_duration - FADE_DURATION_SEC):.2f}s within part2) will be applied to part2 only. \"\n",
" f\"No fade at the mid-video join.\")\n",
" else:\n",
" print(\"🎬 Intro/outro mode active for this video — no fade will be applied to part1/part2.\")\n",
"\n",
" gpu0_id = \"0\"\n",
" gpu1_id = \"1\" if n_gpus >= 2 else \"0\"\n",
" tag2 = \"GPU1\" if n_gpus >= 2 else \"GPU0\"\n",
"\n",
" # part1: fade-in only (start of final video) when in fade mode. No fade-out — mid-video cut.\n",
" extra_inputs1, filter_complex1, vlabel1 = build_logo_filter_complex(\n",
" logo_geo, \"0:v\",\n",
" fade_in=use_fade,\n",
" fade_out_start=None,\n",
" final_crop=final_crop,\n",
" )\n",
" split1 = [\n",
" \"ffmpeg\", \"-y\",\n",
" \"-hwaccel\", \"cuda\", \"-hwaccel_device\", gpu0_id, \"-hwaccel_output_format\", \"cuda\",\n",
" \"-c:v\", decoder,\n",
" ] + crop_resize_args + [\n",
" \"-i\", input_video,\n",
" \"-t\", split_point,\n",
" ] + extra_inputs1 + [\n",
" \"-filter_complex\", filter_complex1,\n",
" \"-map\", vlabel1, \"-map\", \"0:a?\",\n",
" \"-c:v\", \"hevc_nvenc\", \"-gpu\", gpu0_id, \"-preset\", PRESET, \"-cq\", \"18\",\n",
" \"-maxrate\", MAXRATE, \"-bufsize\", BUFSIZE,\n",
" \"-c:a\", \"copy\",\n",
" PART1_PATH\n",
" ]\n",
"\n",
" # part2: fade-out only (end of final video) when in fade mode, timed against part2's OWN duration.\n",
" # No fade-in — this is a mid-video cut continuing from part1.\n",
" extra_inputs2, filter_complex2, vlabel2 = build_logo_filter_complex(\n",
" logo_geo, \"0:v\",\n",
" fade_in=False,\n",
" fade_out_start=(part2_duration - FADE_DURATION_SEC) if use_fade else None,\n",
" final_crop=final_crop,\n",
" )\n",
" split2 = [\n",
" \"ffmpeg\", \"-y\",\n",
" \"-hwaccel\", \"cuda\", \"-hwaccel_device\", gpu1_id, \"-hwaccel_output_format\", \"cuda\",\n",
" \"-c:v\", decoder,\n",
" ] + crop_resize_args + [\n",
" \"-ss\", split_point, \"-i\", input_video,\n",
" ] + extra_inputs2 + [\n",
" \"-filter_complex\", filter_complex2,\n",
" \"-map\", vlabel2, \"-map\", \"0:a?\",\n",
" \"-c:v\", \"hevc_nvenc\", \"-gpu\", gpu1_id, \"-preset\", PRESET, \"-cq\", \"18\",\n",
" \"-maxrate\", MAXRATE, \"-bufsize\", BUFSIZE,\n",
" \"-c:a\", \"copy\",\n",
" PART2_PATH\n",
" ]\n",
"\n",
" start_time = time.time()\n",
" p1, t1, log1 = run_with_progress(split1, \"GPU0\")\n",
" p2, t2, log2 = run_with_progress(split2, tag2)\n",
"\n",
" p1.wait(); t1.join()\n",
" p2.wait(); t2.join()\n",
" print() # move past the live-updating line\n",
"\n",
" if p1.returncode != 0:\n",
" print(\"\\n\".join(log1[-15:])); raise RuntimeError(\"part1 split failed\")\n",
" if p2.returncode != 0:\n",
" print(\"\\n\".join(log2[-15:])); raise RuntimeError(\"part2 split failed\")\n",
"\n",
" elapsed = time.time() - start_time\n",
" print(f\"\\n⏱️ Both GPU jobs finished in {elapsed/60:.2f} min ({elapsed:.1f} sec)\")\n",
"\n",
" # ---- Concatenate (stream copy, identical params so no quality loss) ----\n",
" print(\"🔗 Merging part1 + part2...\")\n",
" with open(LIST_TXT_PATH, \"w\") as f:\n",
" f.write(f\"file '{PART1_PATH}'\\nfile '{PART2_PATH}'\")\n",
"\n",
" merge_target = MAIN_ONLY_PATH if use_intro_outro else FINAL_OUTPUT_PATH\n",
" concat_cmd = [\"ffmpeg\", \"-y\", \"-f\", \"concat\", \"-safe\", \"0\", \"-i\", LIST_TXT_PATH,\n",
" \"-c\", \"copy\", merge_target]\n",
" res = subprocess.run(concat_cmd, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, text=True)\n",
" if res.returncode != 0:\n",
" print(res.stdout)\n",
" raise RuntimeError(\"concat failed\")\n",
"\n",
" # Clean up intermediates (they live in /kaggle/temp anyway, so this is just tidiness)\n",
" for f in (PART1_PATH, PART2_PATH, LIST_TXT_PATH):\n",
" if os.path.exists(f):\n",
" os.remove(f)\n",
"\n",
" if use_intro_outro:\n",
" stitch_intro_outro(MAIN_ONLY_PATH, FINAL_OUTPUT_PATH)\n",
"\n",
" print(\"✅ Done! Frame-accurate split, full GPU pipeline, merged\" +\n",
" (\", intro/outro stitched.\" if use_intro_outro else \", fade-in/out applied.\"))\n",
" print(f\"📦 Final video saved at: {FINAL_OUTPUT_PATH}\")\n",
" total_elapsed = time.time() - overall_start\n",
" print(f\"🏁 TOTAL TIME TAKEN: {total_elapsed/60:.2f} min ({total_elapsed:.1f} sec)\")\n",
"\n",
"if __name__ == \"__main__\":\n",
" CONFIG_PATH = \"/kaggle/input/datasets/joymant/20260629-172948-b2177c/crop_config.json\"\n",
" INPUT_VIDEO_OVERRIDE = \"/kaggle/input/datasets/joymant/20260629-172948-b2177c/output_20260629_172948_b2177c.mkv\"\n",
" parallel_dual_gpu_safe(config_path=CONFIG_PATH, input_video_override=INPUT_VIDEO_OVERRIDE)"
]
}
],
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