From 229cf4dc13f2806afeea3ca784e693866954488c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Adam=20Mlad=C3=BD?= Date: Mon, 23 Dec 2024 17:16:50 +0100 Subject: [PATCH] added a bunch of stuff, release on the way --- .gitignore | 1 - README.md | 98 ++++++++++----- main.py | 116 ++++++++++++------ pymo | Bin 0 -> 6370872 bytes requirements.txt | 4 +- src/__pycache__/differ.cpython-310.pyc | Bin 4672 -> 6460 bytes src/__pycache__/filter_gen.cpython-310.pyc | Bin 1517 -> 3487 bytes .../pycuda_denoise.cpython-310.pyc | Bin 8678 -> 8709 bytes src/cuda/pycuda_denoise.py | 4 +- src/differ.py | 55 +++++++-- src/filter_gen.py | 51 +++++++- weights/README.md | 5 + 12 files changed, 252 insertions(+), 82 deletions(-) create mode 100755 pymo create mode 100644 weights/README.md diff --git a/.gitignore b/.gitignore index 1c5b179..1350556 100644 --- a/.gitignore +++ b/.gitignore @@ -2,5 +2,4 @@ venv main.build dist test -1x-WB-Denoise.pth test.py diff --git a/README.md b/README.md index 65ba152..e870f5a 100644 --- a/README.md +++ b/README.md @@ -1,11 +1,3 @@ - _____ __ __ - | __ \ | \/ | - | |__) | _| \ / | ___ - | ___/ | | | |\/| |/ _ \ - | | | |_| | | | | (_) | - |_| \__, |_| |_|\___/ - __/ | - |___/ # PyMo (Python Motion Visualizer GUI) ### A CLI script for visualizing differences between video frames, eg. motion. @@ -41,24 +33,24 @@ ## Requirements: - Python 3.10 or newer -- Nvidia GPU with installed drivers (Optional but Recommended) +- Nvidia GPU + - Minimum: GTX 1650 4GB + - Recommended: RTX 4060 8GB - At least 16GB of RAM --- ## Installation: ```bash -git clone https://github.com/TheElevatedOne/pymo.git && cd pymo -python3 -m venv venv -source venv/bin/activate -pip install -r requirements.txt +git clone -b 1.0.0 https://github.com/TheElevatedOne/pymo.git && cd pymo +./install-venv.sh ``` --- ## Running: ``` -usage: main.py [-h] -i INPUT [-o OUTPUT] [-n NAME] [-f OFFSET] [-t THREADS] [-s] [-c] [-m MODEL] +usage: pymo [-h] -i INPUT [-o PATH] [-n NAME] [-f INT[1, 50]] [-t CPU[1, 8]] [-s] [-c] [-m {knn,nlm,sr}] [-sr {Directory Empty!}] _____ __ __ | __ \ | \/ | @@ -68,30 +60,47 @@ usage: main.py [-h] -i INPUT [-o OUTPUT] [-n NAME] [-f OFFSET] [-t THREADS] [-s] |_| \__, |_| |_|\___/ __/ | |___/ - + Python Motion Visualizer CLI options: -h, --help show this help message and exit + +Required: + Required Arguments + -i INPUT, --input INPUT Relative path to the Input Video - -o OUTPUT, --output OUTPUT + +Optional: + Optional Arguments + + -o PATH, --output PATH (Optional) Absolute path to output directory -n NAME, --name NAME (Optional) Custom Filename for the video - -f OFFSET, --offset OFFSET + -f INT[1, 50], --offset INT[1, 50] (Optional) Number of Offset Frames [Default = 5] - -t THREADS, --threads THREADS + -t CPU[1, 8], --threads CPU[1, 8] (Optional) Amount of threads to run the process on [Default = 2] -s, --slow_motion (Optional) Sets the FPS of the Output Video to half the original; - Essentially creating a slow-motion of the original without interpolation - -c, --cpu (Optional) Denoising step by default runs on CUDA Acceleration (if Nvidia GPU Available) - Setting this makes it run on CPU even if GPU is Available - -m MODEL, --model MODEL - (Optional) Model to use when denoising via GPU [Default = knn] [Options: nlm, knn] + Essentially creating a slow-motion of the original without interpolation + +Denoising: + Denoising Arguments + + -c, --cpu (Optional) Denoising step by default runs on CUDA Acceleration (if Nvidia GPU Available); + Setting this makes it run on CPU even if GPU is Available + -m {knn,nlm,sr}, --model {knn,nlm,sr} + (Optional) Model to use when denoising via GPU [Default = knn]; + SR - Super Resolution (ESRGAN, SwinIR, ...), + Needs a PyTorch weight file (.pth) in ./weights/ to be active. + -sr {Directory Empty!}, --super_resolution {Directory Empty!} + (Optional) Choosing Weights for SR (if available) + [Default = Directory Empty!] + ``` -### Detailed info on arguments: -- `-i/--input [FILE]` A Video File with OpenCV2 supported extensions +### Detailed info on some arguments: - `-o/--output [PATH]` An absolute path to a directory, e.g. on Linux `/home/${whoami}/directory` - If left empty, it will default to Input Video Dir - `-n/--name [NAME]` Custom name for the output video, without extension. Default is `pymo_{input-vid-name}` @@ -108,7 +117,33 @@ options: - ex. 60 fps Video -> 30 fps Video but Twice the length - `-c/--cpu` The program uses [PyCuda](https://pypi.org/project/pycuda/) for GPU Acceleration on Denoising by default (unless it does not detect a GPU) - This forces the Program to use the CPU, which results in higher quality render, but with a long render time. -- `-m/--model` GPU Denoising Model switcher, both are good for some things +- `-m/--model` GPU Denoising Model switcher. + - KNN/NLM2 are good for some things, they are fast but sacrifice quality. + - SR (Super Resolution) models (or weights) are slower than the above, but faster than CPU and have amazing quality. + - They are trained weights on datasets (AI), which can do many things. I mainly use them to Denoise. + - They need fast GPU's to run and a lot of VRAM. This may be the choice for someone with a good GPU. + - Weights are not packaged with the program, Download them [here](./weights/README.md). + +--- + +## Optimization: +As I develop this project, I try to optimize any algorithm I use after I got it working.
+With that, I just make 80% improvement on the Motion Generation (Difference Blend) and 50% improvement on CPU denoising. + +Current Times (On My Machine): +- Specs: + - CPU - Intel i5-9300H + - GPU - Nvidia GTX 1650 Mobile +- Times (for Compute Intesive Tasks) [using test_01.mp4 | 4K, 210 Frames]: + - Exporting Frames of the Video - 44s + - Motion Generation - 1m 11s + - Contrast Filter - 27s + - Denoising: + - CPU - 6m 2s + - KNN - 44s + - NLM2 - 54s + - SR (1x-WB-Denoise.pth) - 6m 52s + - Encoding Video - 17s --- @@ -120,12 +155,15 @@ options: ## Modules and scripts used: - [**tqdm**](https://pypi.org/project/tqdm/) for progress bars - [**PIL/Pillow**](https://pypi.org/project/pillow/) for easy image transformation -- [**blend-modes**](https://pypi.org/project/blend-modes/) for the difference blend - [**opencv-python**](https://pypi.org/project/opencv-python/) for simpler video transformation, reading, writing and denoising -- [**numpy**](https://pypi.org/project/numpy/) for converting Pillow images to cv2 arrays and vice-versa -- [**pycuda**](https://pypi.org/project/pycuda/) for running GPU-accelerated denoising -- [**torch**](https://pypi.org/project/torch/) just for checking of user has GPU or not +- [**imageio**](https://pypi.org/project/imageio/) for reading and writing images +- [**numpy**](https://pypi.org/project/numpy/) for converting Pillow images to cv2 arrays and vice versa +- [**pycuda**](https://pypi.org/project/pycuda/) for running GPU-accelerated Denoising +- [**torch**](https://pypi.org/project/torch/) for running GPU Super Resolution Models for Denoising +- [**torchvision**](https://pypi.org/project/torchvision/) for converting numpy arrays into tensors and vice versa +- [**spandrel**](https://pypi.org/project/spandrel/) project of chaiNNer developer, for reading all types of SR weights - [**PyCuda_Denoise_Filters**](https://github.com/AlainPaillou/PyCuda_Denoise_Filters) for GPU denoising - Both of the `Mono` scripts were used in my project and were modified to fit the use-case +- [**Nuitka**](https://pypi.org/project/Nuitka/) for compiling `main.py` into a binary for easier running and adding to `$PATH`

\ No newline at end of file diff --git a/main.py b/main.py index e6e4adf..4cc6d51 100644 --- a/main.py +++ b/main.py @@ -1,37 +1,69 @@ import argparse import multiprocessing +import os.path import sys +import termcolor +import traceback from src.differ import Difference def parse() -> argparse.Namespace: - parser = argparse.ArgumentParser(description=""" - _____ __ __ - | __ \ | \/ | - | |__) | _| \ / | ___ - | ___/ | | | |\/| |/ _ \ - | | | |_| | | | | (_) | - |_| \__, |_| |_|\___/ - __/ | - |___/ - - Python Motion Visualizer CLI""", formatter_class=argparse.RawTextHelpFormatter) + """Function for parsing CLI arguments""" + sr_models = [ + os.path.splitext(os.path.basename(x))[0] for x in os.listdir( + os.path.join( + os.path.dirname(__file__), + "weights" + ) + ) if ".pth" in x + ] + sr_models.sort() - parser.add_argument("-i", "--input", required=True, help="""Relative path to the Input Video""", type=str) - parser.add_argument("-o", "--output", required=False, help="(Optional) Absolute path to output directory", type=str, - metavar="PATH") - parser.add_argument("-n", "--name", required=False, help="(Optional) Custom Filename for the video", type=str) - parser.add_argument("-f", "--offset", required=False, default=5, help="(Optional) Number of Offset Frames [Default = 5]", - type=int, choices=range(1, 50), metavar="INT[1, 50]") - parser.add_argument("-t", "--threads", required=False, default=2, help="(Optional) Amount of threads to run the process on [Default = 2]", - type=int, choices=range(1, multiprocessing.cpu_count()), metavar="CPU[1, %d]" % multiprocessing.cpu_count()) - parser.add_argument("-m", "--model", required=False, default="knn", - help="(Optional) Model to use when denoising via GPU [Default = knn]", - choices=["knn", "nlm"]) - parser.add_argument("-s", "--slow_motion", required=False, default=False, help="""(Optional) Sets the FPS of the Output Video to half the original; + if not len(sr_models): + sr_models.append("Directory Empty!") + + parser = argparse.ArgumentParser(description=" " + termcolor.colored(" _____ ", "light_blue", attrs=["bold"]) + termcolor.colored("__ __ ", "light_green", attrs=["bold"]) + "\n" + \ + " " + termcolor.colored("| __ \ ", "light_blue", attrs=["bold"]) + termcolor.colored("| \/ | ", "light_green", attrs=["bold"]) + "\n" + \ + " " + termcolor.colored("| |__) | _", "light_blue", attrs=["bold"]) + termcolor.colored("| \ / | ___ ", "light_green", attrs=["bold"]) + "\n" + \ + " " + termcolor.colored("| ___/ | | |", "light_blue", attrs=["bold"]) + termcolor.colored(" |\/| |/ _ \ ", "light_green", attrs=["bold"]) + "\n" + \ + " " + termcolor.colored("| | | |_| |", "light_blue", attrs=["bold"]) + termcolor.colored(" | | | (_) |", "light_green", attrs=["bold"]) + "\n" + \ + " " + termcolor.colored("|_| \__, |", "light_blue", attrs=["bold"]) + termcolor.colored("_| |_|\___/ ", "light_green", attrs=["bold"]) + "\n" + \ + " " + termcolor.colored(" __/ |", "light_blue", attrs=["bold"]) + termcolor.colored(" ", "light_green", attrs=["bold"]) + "\n" + \ + " " + termcolor.colored(" |___/ ", "light_blue", attrs=["bold"]) + termcolor.colored(" ", "light_green", attrs=["bold"]) + "\n\n" + \ + " " + termcolor.colored("Python ", "light_blue", attrs=["bold"]) + termcolor.colored("Motion ", "light_green", attrs=["bold"]) + \ + termcolor.colored("Visualizer CLI", "white", attrs=["bold"]), formatter_class=argparse.RawTextHelpFormatter) + + required = parser.add_argument_group("Required", "Required Arguments") + optional = parser.add_argument_group("Optional", "Optional Arguments") + denoise = parser.add_argument_group("Denoising", description="Denoising Arguments") + required.add_argument("-i", "--input", required=True, + help="""Relative path to the Input Video""", type=str) + optional.add_argument("-o", "--output", required=False, + help="(Optional) Absolute path to output directory", type=str,metavar="PATH") + optional.add_argument("-n", "--name", required=False, help="(Optional) Custom Filename for the video", + type=str) + optional.add_argument("-f", "--offset", required=False, default=5, + help="(Optional) Number of Offset Frames [Default = 5]",type=int, choices=range(1, 50), + metavar="INT[1, 50]") + optional.add_argument("-t", "--threads", required=False, default=2, + help="(Optional) Amount of threads to run the process on [Default = 2]", + type=int, choices=range(1, multiprocessing.cpu_count()), + metavar="CPU[1, %d]" % multiprocessing.cpu_count()) + optional.add_argument("-s", "--slow_motion", required=False, default=False, + help="""(Optional) Sets the FPS of the Output Video to half the original; Essentially creating a slow-motion of the original without interpolation""", action="store_true") - parser.add_argument("-c", "--cpu", required=False, default=False, help="""(Optional) Denoising step by default runs on CUDA Acceleration (if Nvidia GPU Available); + denoise.add_argument("-c", "--cpu", required=False, default=False, + help="""(Optional) Denoising step by default runs on CUDA Acceleration (if Nvidia GPU Available); Setting this makes it run on CPU even if GPU is Available""", action="store_true") + denoise.add_argument("-m", "--model", required=False, default="knn", + help="""(Optional) Model to use when denoising via GPU [Default = knn]; + SR - Super Resolution (ESRGAN, SwinIR, ...), + Needs a PyTorch weight file (.pth) in ./weights/ to be active.""", + choices=["knn", "nlm", "sr"]) + denoise.add_argument("-sr", "--super_resolution", required=False, + help=f'''(Optional) Choosing Weights for SR (if available) + [Default = {sr_models[0]}]''', + choices=sr_models, default=sr_models[0]) if len(sys.argv) == 1: parser.print_help(sys.stderr) @@ -41,18 +73,19 @@ def parse() -> argparse.Namespace: def main() -> None: args = parse() # Parse CLI Arguments - print(""" - _____ __ __ - | __ \ | \/ | - | |__) | _| \ / | ___ - | ___/ | | | |\/| |/ _ \ - | | | |_| | | | | (_) | - |_| \__, |_| |_|\___/ - __/ | - |___/ -----------------------------------""") + print(" " + termcolor.colored(" _____ ", "light_blue", attrs=["bold"]) + termcolor.colored("__ __ ", "light_green", attrs=["bold"]) + "\n" + \ + " " + termcolor.colored("| __ \ ", "light_blue", attrs=["bold"]) + termcolor.colored("| \/ | ", "light_green", attrs=["bold"]) + "\n" + \ + " " + termcolor.colored("| |__) | _", "light_blue", attrs=["bold"]) + termcolor.colored("| \ / | ___ ", "light_green", attrs=["bold"]) + "\n" + \ + " " + termcolor.colored("| ___/ | | |", "light_blue", attrs=["bold"]) + termcolor.colored(" |\/| |/ _ \ ", "light_green", attrs=["bold"]) + "\n" + \ + " " + termcolor.colored("| | | |_| |", "light_blue", attrs=["bold"]) + termcolor.colored(" | | | (_) |", "light_green", attrs=["bold"]) + "\n" + \ + " " + termcolor.colored("|_| \__, |", "light_blue", attrs=["bold"]) + termcolor.colored("_| |_|\___/ ", "light_green", attrs=["bold"]) + "\n" + \ + " " + termcolor.colored(" __/ |", "light_blue", attrs=["bold"]) + termcolor.colored(" ", "light_green", attrs=["bold"]) + "\n" + \ + " " + termcolor.colored(" |___/ ", "light_blue", attrs=["bold"]) + termcolor.colored(" ", "light_green", attrs=["bold"]) + "\n\n" + \ + " " + termcolor.colored("Python ", "light_blue", attrs=["bold"]) + termcolor.colored("Motion ", "light_green", attrs=["bold"]) + \ + termcolor.colored("Visualizer CLI", "white", attrs=["bold"]) + "\n") print("Initializing") - di = Difference(args.input, args.output, args.name, args.offset, args.threads, args.slow_motion, args.cpu, args.model) # Initialize imported module + di = Difference(args.input, args.output, args.name, args.offset, args.threads, + args.slow_motion, args.cpu, args.model, args.super_resolution) # Initialize imported module print("Creating Temporary Files Directory") print("----------------------------------") try: @@ -62,15 +95,22 @@ def main() -> None: print("02. Difference Generation") di.dif_frames() print("03. Post Processing") - di.gen_video() + output = di.gen_video() print(" 02. Removing Temporary Directory") di.temp_dir() + print("----------------------------------") + print(termcolor.colored("Finished!", "light_green", attrs=["bold"])) + print(f"Video rendered at {termcolor.colored(output, color='light_yellow')}") except Exception as e: di.temp_dir() print("----------------------------------") - print("Program Failed on Runtime due to Exception:") - print(e) + print(f">>> {termcolor.colored('Program Failed on Runtime due to Exception:', 'red', 'on_black', ['bold'])}") + print(f">>> {termcolor.colored(e, on_color='on_black', attrs=['bold'])}") + traceback.print_exc() except KeyboardInterrupt: + print("----------------------------------") + print(f">>> {termcolor.colored('KeyboardInterrupt', 'cyan', attrs=['bold'])}") + print(">>> Removing Temporary Directory") di.temp_dir() sys.exit(130) diff --git a/pymo b/pymo new file mode 100755 index 0000000000000000000000000000000000000000..2e0d2492361db0e3f0aebbd78a40f7e79fc8f358 GIT binary patch literal 6370872 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