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* chore: update versions (#9168) Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> * chore: update error.svx (#9291) * chore: update error.svx occured -> occurred * add changeset --------- Co-authored-by: gradio-pr-bot <gradio-pr-bot@users.noreply.github.com> * Update docs to use new Image init (#9304) * Fix scrollbars everywhere (#9276) * changes * add changeset * scroll fix * remove .json css, adjust scroll height to account for label --------- Co-authored-by: Ali Abid <aliabid94@gmail.com> Co-authored-by: gradio-pr-bot <gradio-pr-bot@users.noreply.github.com> Co-authored-by: Hannah <hannahblair@users.noreply.github.com> * Separate starlette.Request from PredictBody. Only set in new PredictBodyInternal object (#9279) * use custom pydantic type annotatio * add changeset * Add code * add changeset * rework * dont use arbitrary_types_allowed * add changeset * fix test * revert path change --------- Co-authored-by: gradio-pr-bot <gradio-pr-bot@users.noreply.github.com> * Add root_url to components created by gr.render (#9267) * Fix bug * add changeset --------- Co-authored-by: gradio-pr-bot <gradio-pr-bot@users.noreply.github.com> * Fileformat whitelist (#9302) * changes * add changeset * Update routes.py --------- Co-authored-by: Ali Abid <aliabid94@gmail.com> Co-authored-by: gradio-pr-bot <gradio-pr-bot@users.noreply.github.com> * Fix multiple trigger bug when function has js (#9188) * add code * add changeset * lint --------- Co-authored-by: gradio-pr-bot <gradio-pr-bot@users.noreply.github.com> * chore: update versions (#9298) Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> * fix json * harden test * harden test * clean * format * add changeset * notebooks * fix old conflicts --------- Co-authored-by: Gradio PR Bot <121576822+gradio-pr-bot@users.noreply.github.com> Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Ikko Eltociear Ashimine <eltociear@gmail.com> Co-authored-by: gradio-pr-bot <gradio-pr-bot@users.noreply.github.com> Co-authored-by: Tayfun Sen <tayfun.sen@gmail.com> Co-authored-by: aliabid94 <aabid94@gmail.com> Co-authored-by: Ali Abid <aliabid94@gmail.com> Co-authored-by: Hannah <hannahblair@users.noreply.github.com> Co-authored-by: Freddy Boulton <alfonsoboulton@gmail.com>
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{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: stream_video_out"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio opencv-python"]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "os.mkdir('video')\n", "!wget -q -O video/compliment_bot_screen_recording_3x.mp4 https://github.com/gradio-app/gradio/raw/main/demo/stream_video_out/video/compliment_bot_screen_recording_3x.mp4"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import cv2\n", "import os\n", "from pathlib import Path\n", "import atexit\n", "\n", "current_dir = Path(__file__).resolve().parent\n", "\n", "\n", "def delete_files():\n", " for p in Path(current_dir).glob(\"*.ts\"):\n", " p.unlink()\n", " for p in Path(current_dir).glob(\"*.mp4\"):\n", " p.unlink()\n", "\n", "atexit.register(delete_files)\n", "\n", "\n", "def process_video(input_video, stream_as_mp4):\n", " cap = cv2.VideoCapture(input_video)\n", "\n", " video_codec = cv2.VideoWriter_fourcc(*\"mp4v\") if stream_as_mp4 else cv2.VideoWriter_fourcc(*\"x264\") # type: ignore\n", " fps = int(cap.get(cv2.CAP_PROP_FPS))\n", " width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))\n", " height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))\n", "\n", " iterating, frame = cap.read()\n", "\n", " n_frames = 0\n", " n_chunks = 0\n", " name = str(current_dir / f\"output_{n_chunks}{'.mp4' if stream_as_mp4 else '.ts'}\")\n", " segment_file = cv2.VideoWriter(name, video_codec, fps, (width, height)) # type: ignore\n", "\n", " while iterating:\n", "\n", " # flip frame vertically\n", " frame = cv2.flip(frame, 0)\n", " display_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)\n", " segment_file.write(display_frame)\n", " n_frames += 1\n", " if n_frames == 3 * fps:\n", " n_chunks += 1\n", " segment_file.release()\n", " n_frames = 0\n", " yield name\n", " name = str(current_dir / f\"output_{n_chunks}{'.mp4' if stream_as_mp4 else '.ts'}\")\n", " segment_file = cv2.VideoWriter(name, video_codec, fps, (width, height)) # type: ignore\n", "\n", " iterating, frame = cap.read()\n", "\n", " segment_file.release()\n", " yield name\n", "\n", "with gr.Blocks() as demo:\n", " gr.Markdown(\"# Video Streaming Out \ud83d\udcf9\")\n", " with gr.Row():\n", " with gr.Column():\n", " input_video = gr.Video(label=\"input\")\n", " checkbox = gr.Checkbox(label=\"Stream as MP4 file?\", value=False)\n", " with gr.Column():\n", " processed_frames = gr.Video(label=\"stream\", streaming=True, autoplay=True, elem_id=\"stream_video_output\")\n", " with gr.Row():\n", " process_video_btn = gr.Button(\"process video\")\n", "\n", " process_video_btn.click(process_video, [input_video, checkbox], [processed_frames])\n", "\n", " gr.Examples(\n", " [[os.path.join(os.path.abspath(''), \"video/compliment_bot_screen_recording_3x.mp4\"), False],\n", " [os.path.join(os.path.abspath(''), \"video/compliment_bot_screen_recording_3x.mp4\"), True]],\n", " [input_video, checkbox],\n", " fn=process_video,\n", " outputs=processed_frames,\n", " cache_examples=False,\n", " )\n", "\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} | ||
{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: stream_video_out"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio opencv-python"]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/stream_video_out/output_0.mp4\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/stream_video_out/output_0.ts\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/stream_video_out/output_1.mp4\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/stream_video_out/output_1.ts\n", "os.mkdir('video')\n", "!wget -q -O video/compliment_bot_screen_recording_3x.mp4 https://github.com/gradio-app/gradio/raw/main/demo/stream_video_out/video/compliment_bot_screen_recording_3x.mp4"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import cv2\n", "import os\n", "from pathlib import Path\n", "import atexit\n", "\n", "current_dir = Path(__file__).resolve().parent\n", "\n", "\n", "def delete_files():\n", " for p in Path(current_dir).glob(\"*.ts\"):\n", " p.unlink()\n", " for p in Path(current_dir).glob(\"*.mp4\"):\n", " p.unlink()\n", "\n", "atexit.register(delete_files)\n", "\n", "\n", "def process_video(input_video, stream_as_mp4):\n", " cap = cv2.VideoCapture(input_video)\n", "\n", " video_codec = cv2.VideoWriter_fourcc(*\"mp4v\") if stream_as_mp4 else cv2.VideoWriter_fourcc(*\"x264\") # type: ignore\n", " fps = int(cap.get(cv2.CAP_PROP_FPS))\n", " width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))\n", " height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))\n", "\n", " iterating, frame = cap.read()\n", "\n", " n_frames = 0\n", " n_chunks = 0\n", " name = str(current_dir / f\"output_{n_chunks}{'.mp4' if stream_as_mp4 else '.ts'}\")\n", " segment_file = cv2.VideoWriter(name, video_codec, fps, (width, height)) # type: ignore\n", "\n", " while iterating:\n", "\n", " # flip frame vertically\n", " frame = cv2.flip(frame, 0)\n", " display_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)\n", " segment_file.write(display_frame)\n", " n_frames += 1\n", " if n_frames == 3 * fps:\n", " n_chunks += 1\n", " segment_file.release()\n", " n_frames = 0\n", " yield name\n", " name = str(current_dir / f\"output_{n_chunks}{'.mp4' if stream_as_mp4 else '.ts'}\")\n", " segment_file = cv2.VideoWriter(name, video_codec, fps, (width, height)) # type: ignore\n", "\n", " iterating, frame = cap.read()\n", "\n", " segment_file.release()\n", " yield name\n", "\n", "with gr.Blocks() as demo:\n", " gr.Markdown(\"# Video Streaming Out \ud83d\udcf9\")\n", " with gr.Row():\n", " with gr.Column():\n", " input_video = gr.Video(label=\"input\")\n", " checkbox = gr.Checkbox(label=\"Stream as MP4 file?\", value=False)\n", " with gr.Column():\n", " processed_frames = gr.Video(label=\"stream\", streaming=True, autoplay=True, elem_id=\"stream_video_output\")\n", " with gr.Row():\n", " process_video_btn = gr.Button(\"process video\")\n", "\n", " process_video_btn.click(process_video, [input_video, checkbox], [processed_frames])\n", "\n", " gr.Examples(\n", " [[os.path.join(os.path.abspath(''), \"video/compliment_bot_screen_recording_3x.mp4\"), False],\n", " [os.path.join(os.path.abspath(''), \"video/compliment_bot_screen_recording_3x.mp4\"), True]],\n", " [input_video, checkbox],\n", " fn=process_video,\n", " outputs=processed_frames,\n", " cache_examples=False,\n", " )\n", "\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5} |
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