mirror of
https://github.com/PhotonVision/photonvision
synced 2026-06-19 00:41:41 +00:00
Update notebook links (#2037)
This commit is contained in:
Rikhil Chilka
@@ -16,33 +16,44 @@ comma_sep_yolo_versions = ", ".join(valid_yolo_versions)
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ultralytics_folder_name_yolov5 = "airockchip_yolo_pkg_yolov5"
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ultralytics_default_folder_name = "airockchip_yolo_pkg"
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bad_model_msg = """
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This is usually due to passing in the wrong model version.
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Please make sure you have the right model version and try again.
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"""
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# idk how else to make Google Colab display this nicely
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class IncorrectModelError(Exception):
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def __init__(self, message):
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self.message = message
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super().__init__(self.message)
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def print_bad_model_msg(cause):
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print(f"{cause}{bad_model_msg}")
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def check_git_installed():
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def run_and_exit_with_error(cmd, error_msg, enable_error_output=True):
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try:
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subprocess.run(["git", "--version"]).check_returncode()
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except:
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print("Git is not installed or not found in your PATH.")
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print("Please install Git from https://git-scm.com/downloads and try again.")
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if enable_error_output:
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subprocess.run(
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cmd,
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stderr=subprocess.STDOUT,
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stdout=subprocess.PIPE,
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universal_newlines=True,
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).check_returncode()
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else:
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subprocess.run(cmd).check_returncode()
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except subprocess.CalledProcessError as e:
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print(error_msg)
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if enable_error_output:
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print(e.stdout)
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sys.exit(1)
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def check_git_installed():
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run_and_exit_with_error(
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["git", "--version"],
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"""Git is not installed or not found in your PATH.
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Please install Git from https://git-scm.com/downloads and try again.""",
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)
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def check_or_clone_rockchip_repo(repo_url, repo_name=ultralytics_default_folder_name):
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if os.path.exists(repo_name):
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print(
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@@ -50,23 +61,18 @@ def check_or_clone_rockchip_repo(repo_url, repo_name=ultralytics_default_folder_
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)
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else:
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print(f'Cloning Rockchip repo to "{repo_name}"')
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try:
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subprocess.run(["git", "clone", repo_url, repo_name]).check_returncode()
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except subprocess.CalledProcessError as e:
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print("Failed to clone Rockchip repo, see error output below")
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print(e.output)
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sys.exit(1)
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run_and_exit_with_error(
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["git", "clone", repo_url, repo_name],
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"Failed to clone Rockchip repo, please see error output",
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)
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def run_pip_install_or_else_exit(args):
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print("Running pip install...")
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try:
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subprocess.run(["pip", "install"] + args).check_returncode()
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except subprocess.CalledProcessError as e:
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print("Pip install rockchip repo failed, see error output")
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print(e.output)
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sys.exit(1)
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run_and_exit_with_error(
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["pip", "install"] + args,
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"Pip install rockchip repo failed, please see error output",
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)
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def run_onnx_conversion_yolov5(model_path):
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@@ -93,23 +99,22 @@ def run_onnx_conversion_yolov5(model_path):
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"--include",
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"onnx",
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],
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capture_output=True,
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text=True,
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stderr=subprocess.STDOUT,
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stdout=subprocess.PIPE,
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universal_newlines=True,
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).check_returncode()
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except subprocess.CalledProcessError as e:
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print("Failed to run YOLOv5 export, see output below")
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output_string = (e.stdout or "") + (e.stderr or "")
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print(output_string)
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print("Failed to run YOLOv5 export, please see error output")
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if "ModuleNotFoundError" in output_string and "ultralytics" in output_string:
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if "ModuleNotFoundError" in e.stdout and "ultralytics" in e.stdout:
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print_bad_model_msg(
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"It seems the YOLOv5 repo could not find an ultralytics installation."
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)
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elif (
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"AttributeError" in output_string
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and "_register_detect_seperate" in output_string
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):
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elif "AttributeError" in e.stdout and "_register_detect_seperate" in e.stdout:
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print_bad_model_msg("It seems that you received a model attribute error.")
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else:
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print("Unknown Error when converting:")
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print(e.stdout)
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sys.exit(1)
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@@ -132,7 +137,7 @@ def run_onnx_conversion_no_anchor(model_path):
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"Ultralytics has detected that this model is a YOLOv5 model."
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)
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else:
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print(e)
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raise e
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sys.exit(1)
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@@ -37,11 +37,11 @@
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"# DO NOT modify the filenames\n",
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"scripts = [\n",
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" {\n",
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" \"url\": \"https://raw.githubusercontent.com/boomermath/photonvision_rknn_fork/refs/heads/rknn_conversion_tool/scripts/rknn-convert-tool/create_onnx.py\",\n",
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" \"url\": \"https://raw.githubusercontent.com/PhotonVision/photonvision/ba1c0db7e19db090ca04a8375255b00db2e0babd/scripts/rknn-convert-tool/create_onnx.py\",\n",
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" \"filename\": \"create_onnx.py\" # CREATE_ONNX_SCRIPT\n",
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" },\n",
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" {\n",
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" \"url\": \"https://raw.githubusercontent.com/boomermath/photonvision_rknn_fork/refs/heads/rknn_conversion_tool/scripts/rknn-convert-tool/create_rknn.py\",\n",
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" \"url\": \"https://raw.githubusercontent.com/PhotonVision/photonvision/ba1c0db7e19db090ca04a8375255b00db2e0babd/scripts/rknn-convert-tool/create_rknn.py\",\n",
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" \"filename\": \"create_rknn.py\" # CREATE_RKNN_SCRIPT\n",
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" }\n",
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"]\n",
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@@ -254,7 +254,7 @@
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"| `--img_dir` (`-d`) | `str` (required) | Path to your image directory. This can either be a folder of images **or** a dataset folder with a `data.yaml`. |\n",
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"| `--model_path` (`-m`) | `str` (required) | Path to your YOLO ONNX model, created in Step 1. |\n",
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"| `--num_imgs` (`-ni`) | `int` (default: `300`) | Number of images to use for quantization calibration. |\n",
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"| `--disable_quantize` (`-dq`) | `bool` (default: `False`) | Set to `True` to skip quantization entirely, not recommended for performance. |\n",
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"| `--disable_quantize` (`-dq`) | `bool` (default: `False`) | Set to `True` to skip quantization entirely. Not recommended for performance, and should not be used for deployment on PhotonVision, which requires quantization. |\n",
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"| `--rknn_output` (`-o`) | `str` (default: `out.rknn`) | File path where the final RKNN model should be saved. |\n",
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"| `--img_dataset_txt` (`-ds`) | `str` (default: `imgs.txt`) | File path to store the list of images used during quantization. |\n",
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"| `--verbose` (`-vb`) | `bool` (default: `False`) | Enable detailed logging from the RKNN API during conversion. |\n",
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@@ -262,7 +262,7 @@
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"\n",
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"##### *Notes*\n",
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"\n",
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"1. This script is designed for use with [PhotonVision](https://photonvision.org), and by default sets the target platform for RKNN conversion to `RK3588`, a chipset commonly found in many variants of the Orange Pi 5 series (e.g., Orange Pi 5, 5 Pro, 5 Plus, 5 Max, etc.). You may modify the `TARGET_PLATFORM` value in the `create_onnx.py` script to match your specific hardware or deployment requirements if necessary.\n",
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"1. This script is designed for use with [PhotonVision](https://photonvision.org), and by default sets the target platform for RKNN conversion to `RK3588`, a chipset commonly found in many variants of the Orange Pi 5 series (e.g., Orange Pi 5, 5 Pro, 5 Plus, 5 Max, etc.). You may modify the `DEFAULT_PLATFORM` value in the `create_rknn.py` script to match your specific hardware or deployment requirements if necessary.\n",
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"\n",
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"2. If you followed the Roboflow dataset download instructions from the previous section, the dataset will have been extracted to your **current working directory**. In that case, you can simply set `--img_dir` to \"`.`\" to reference the current directory."
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]
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