This commit is contained in:
Nicolas Mowen 2025-05-09 07:26:45 -06:00
parent 37460a4eec
commit 36d3a2792f
3 changed files with 6 additions and 7 deletions

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@ -107,17 +107,17 @@ When choosing images to include in the face training set it is recommended to al
### Step 1 - Building a Strong Foundation
When first enabling face recognition it is important to build a foundation of strong images. It is recommended to start by uploading 1-5 "portrait" photos for each person. It is important that the person's face in the photo is straight-on and not turned which will ensure a good starting point.
When first enabling face recognition it is important to build a foundation of strong images. It is recommended to start by uploading 1-5 photos containing just this person's face. It is important that the person's face in the photo is front-facing and not turned, this will ensure a good starting point.
Then it is recommended to use the `Face Library` tab in Frigate to select and train images for each person as they are detected. When building a strong foundation it is strongly recommended to only train on images that are straight-on. Ignore images from cameras that recognize faces from an angle.
Then it is recommended to use the `Face Library` tab in Frigate to select and train images for each person as they are detected. When building a strong foundation it is strongly recommended to only train on images that are front-facing. Ignore images from cameras that recognize faces from an angle.
Aim to strike a balance between the quality of images while also having a range of conditions (day / night, different weather conditions, different times of day, etc.) in order to have diversity in the images used for each person and not have over-fitting.
Once a person starts to be consistently recognized correctly on images that are straight-on, it is time to move on to the next step.
Once a person starts to be consistently recognized correctly on images that are front-facing, it is time to move on to the next step.
### Step 2 - Expanding The Dataset
Once straight-on images are performing well, start choosing slightly off-angle images to include for training. It is important to still choose images where enough face detail is visible to recognize someone.
Once front-facing images are performing well, start choosing slightly off-angle images to include for training. It is important to still choose images where enough face detail is visible to recognize someone.
## FAQ

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@ -127,8 +127,7 @@ class ModelConfig(BaseModel):
return
# ensure that model cache dir exists
if not os.path.exists(MODEL_CACHE_DIR):
os.makedirs(MODEL_CACHE_DIR)
os.makedirs(MODEL_CACHE_DIR, exist_ok=True)
model_id = self.path[7:]
self.path = os.path.join(MODEL_CACHE_DIR, model_id)

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@ -29,7 +29,7 @@
"uploadFace": "Upload Face Image",
"nextSteps": "Next Steps",
"description": {
"uploadFace": "Upload an image of {{name}}. This should be an image including their face straight-on. Note that the image does not need to be cropped to just their face.",
"uploadFace": "Upload an image of {{name}} that shows their face from a front-facing angle. The image does not need to be cropped to just their face."
}
},
"train": {