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updated API_KEY to ROBOFLOW_API_KEY for clarity #202

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merged 3 commits into from
Dec 20, 2023
Merged

updated API_KEY to ROBOFLOW_API_KEY for clarity #202

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4a44cc1
updated API_KEY to ROBOFLOW_API_KEY for clarity
josephofiowa Dec 20, 2023
08b145b
updated requirements install to assume local position for installation
josephofiowa Dec 20, 2023
983bac2
updated the gaze.py docs example to use ROBOFLOW_API_KEY as well
josephofiowa Dec 20, 2023
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6 changes: 3 additions & 3 deletions docs/foundation/gaze.md
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Original file line number Diff line number Diff line change
Expand Up @@ -26,18 +26,18 @@ import requests
import os

IMG_PATH = "image.jpg"
API_KEY = os.environ["API_KEY"]
ROBOFLOW_API_KEY = os.environ["ROBOFLOW_API_KEY"]
DISTANCE_TO_OBJECT = 1000 # mm
HEIGHT_OF_HUMAN_FACE = 250 # mm
GAZE_DETECTION_URL = "http://127.0.0.1:9001/gaze/gaze_detection?api_key=" + API_KEY
GAZE_DETECTION_URL = "http://127.0.0.1:9001/gaze/gaze_detection?api_key=" + ROBOFLOW_API_KEY

def detect_gazes(frame: np.ndarray):
img_encode = cv2.imencode(".jpg", frame)[1]
img_base64 = base64.b64encode(img_encode)
resp = requests.post(
GAZE_DETECTION_URL,
json={
"api_key": API_KEY,
"api_key": ROBOFLOW_API_KEY,
"image": {"type": "base64", "value": img_base64.decode("utf-8")},
},
)
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4 changes: 2 additions & 2 deletions examples/gaze-detection/README.md
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Expand Up @@ -13,12 +13,12 @@ git clone https://github.com/roboflow/inference
cd inference/examples/gaze-detection
```

Next, set up a Python environment and install the required project dependencies:
Next, set up a Python environment and install the required project dependencies (this assumes running these bash commands from the above terminal window install):

```bash
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
pip install -r ../../requirements/_requirements.txt
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Not tested that but I was always thinking that for gaze to work we need also ../../requirements/requirements.gaze.txt - at least this is suggested by setup.py extras that we created to build libs

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For now, only these are required in gaze.py:

import base64
import cv2
import numpy as np
import requests
import os

We can assume the user is installing inference, overall, and have them setup the base _requirements.txt. In the future, we can decide to scope to individual examples.

```

Next, set up a Roboflow Inference Docker container. This Docker container will manage inference for the gaze detection system. [Learn how to set up an Inference Docker container](https://inference.roboflow.com/quickstart/docker/).
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6 changes: 3 additions & 3 deletions examples/gaze-detection/gaze.py
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Expand Up @@ -6,10 +6,10 @@
import os

IMG_PATH = "image.jpg"
API_KEY = os.environ["API_KEY"]
ROBOFLOW_API_KEY = os.environ["ROBOFLOW_API_KEY"]
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This value is fine, as we also allow it in other places as an alternative for API_KEY - in long ran we may decide on single one

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Let's use ROBOFLOW_API_KEY across docs. Good note that the API_KEY = os.environ["API_KEY"]
here needs to be updated: https://inference.roboflow.com/foundation/gaze/#how-to-use-l2cs-net

DISTANCE_TO_OBJECT = 1000 # mm
HEIGHT_OF_HUMAN_FACE = 250 # mm
GAZE_DETECTION_URL = "http://127.0.0.1:9001/gaze/gaze_detection?api_key=" + API_KEY
GAZE_DETECTION_URL = "http://127.0.0.1:9001/gaze/gaze_detection?api_key=" + ROBOFLOW_API_KEY


def detect_gazes(frame: np.ndarray):
Expand All @@ -18,7 +18,7 @@ def detect_gazes(frame: np.ndarray):
resp = requests.post(
GAZE_DETECTION_URL,
json={
"api_key": API_KEY,
"api_key": ROBOFLOW_API_KEY,
"image": {"type": "base64", "value": img_base64.decode("utf-8")},
},
)
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