AssertionError in DeepFace installation: dependency conflicts and solutions

When installing the DeepFace library, users may encounter AssertionError, which is usually caused by a conflict between the library version and the system or other dependent libraries. This article provides a practical method to solve this problem by specifying old versions of DeepFace and dlib and disabling DeepFace's dependent installation, ensuring a smooth installation under specific system environments.

AssertionError analysis in DeepFace installation

When using pip to install the deep learning face recognition library DeepFace, some users may encounter AssertionError. This error usually occurs during the dependency resolution phase of pip, prompting that assert len(weights) == expected_node_count failed. This indicates that pip encountered inconsistencies when trying to build the dependency graph and was unable to correctly determine the installation order. The same error may occur even when trying to clone from source and install locally using pip install -e .

Root cause of the problem: Dependency conflict

According to experience, this type of AssertionError is often not a logical error in the code itself, but is caused by version incompatibilities or conflicts between the latest version of the DeepFace library and some of its dependencies (such as dlib) or other libraries in the current system environment. When pip tries to resolve these complex dependencies, it may throw assertion errors because it cannot find a solution that satisfies all conditions. In particular, problems arise when a specific version of DeepFace requires a specific range of dependency versions that conflicts with other libraries installed on the system or with the operating system's default library versions.

Solution: Version Backtracking and Dependency Management

An effective way to solve this type of problem is to accurately control the versions of DeepFace and its key dependent libraries. You can bypass pip's dependency resolution dilemma by installing an older version that is known to be compatible and avoiding DeepFace automatically installing its potentially conflicting dependencies.

Here are the specific steps to resolve this issue:

1. Uninstall existing DeepFace versions (if installed) To ensure a clean installation environment, first uninstall any DeepFace versions that may already exist.

    pip uninstall deepface -y

2. Install the specified version of dlib. dlib is an important dependency of DeepFace, and its version compatibility is crucial. Install an older version of dlib that is compatible with the target DeepFace version.

    pip install dlib==19.24.0

   Note: The installation of dlib may require compilation. Make sure your system has the necessary compilation tools (such as build-essential, cmake, etc.) installed.

3. The key step in installing a specific version of DeepFace (without dependencies) is to install an older version of DeepFace and explicitly instruct pip not to install its dependencies (--no-deps). This is because we have manually installed compatible dlibs and want to avoid DeepFace automatically pulling new version dependencies that may cause conflicts.

    pip install --no-deps deepface==0.0.79

Sample code

Putting the above steps together, the complete solution command is as follows:

 # 1. Uninstall the old version of deepface that may exist pip uninstall deepface -y

# 2. Install a compatible dlib version # Note: dlib installation may require compilation tools, please ensure that the system has been installed.
# For example, on Ubuntu/Debian system: sudo apt update && sudo apt install build-essential cmake
pip install dlib==19.24.0

# 3. Install the specified version of deepface and disable its dependency installation pip install --no-deps deepface==0.0.79

Notes and Compatibility

• System environment reference: This solution was successfully verified on a specific Pop!_OS 22.04 LTS x86_64 system using Python 3.10.12 and pip 22.0.2, equipped with an NVIDIA GPU (driver 545.29.06, CUDA 12.3, Torch 2.1.1 cu121). Your system environment may be different, so the specific version number above may need to be fine-tuned based on your actual situation.
• Version selection: deepface==0.0.79 and dlib==19.24.0 are version combinations that have been verified to work together. If DeepFace releases a new version that fixes dependency conflicts in the future, or you need to use the latest features of DeepFace, it is recommended to consult DeepFace's official documentation or GitHub repository to learn about its recommended dependency versions.
• Compiling Dlib: Installation of dlib usually involves compilation of C code. If you encounter dlib installation failure, please check whether your system has cmake, C compiler (such as g) and Python development header files installed.
• Virtual environment: It is strongly recommended to install and manage libraries in an independent Python virtual environment (such as venv or conda) to avoid dependency conflicts between different projects.

Summarize

When a DeepFace installation encounters an AssertionError, it usually points to a complex dependency conflict. This type of installation problem can be effectively solved by strategically backtracking DeepFace and its core dependencies (such as dlib) to older versions that are known to be compatible, and leveraging the --no-deps option to avoid automatically pulling new dependencies that may conflict. When performing such operations, be sure to pay attention to the compatibility of the system environment and give priority to performing it in an isolated virtual environment.

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