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Merge pull request #1383 from serengil/feat-task-0911-file-input-for-api

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Feat task 0911 file input for api
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Sefik Ilkin Serengil 2024-11-10 18:55:43 +00:00 committed by GitHub
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8 changed files with 408 additions and 75 deletions
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2
.github/workflows/tests.yml vendored
View File

@ -37,6 +37,8 @@ jobs:
run: |
python -m pip install --upgrade pip
pip install pytest
# sending files in form data throwing error in flask 3 while running tests
pip install Werkzeug==2.0.2 flask==2.0.2
pip install .
- name: Test with pytest

2
README.md
View File

@ -341,7 +341,7 @@ cd scripts
<p align="center"><img src="https://raw.githubusercontent.com/serengil/deepface/master/icon/deepface-api.jpg" width="90%" height="90%"></p>
Face recognition, facial attribute analysis and vector representation functions are covered in the API. You are expected to call these functions as http post methods. Default service endpoints will be `http://localhost:5005/verify` for face recognition, `http://localhost:5005/analyze` for facial attribute analysis, and `http://localhost:5005/represent` for vector representation. You can pass input images as exact image paths on your environment, base64 encoded strings or images on web. [Here](https://github.com/serengil/deepface/tree/master/deepface/api/postman), you can find a postman project to find out how these methods should be called.
Face recognition, facial attribute analysis and vector representation functions are covered in the API. You are expected to call these functions as http post methods. Default service endpoints will be `http://localhost:5005/verify` for face recognition, `http://localhost:5005/analyze` for facial attribute analysis, and `http://localhost:5005/represent` for vector representation. The API accepts images as file uploads (via form data), or as exact image paths, URLs, or base64-encoded strings (via either JSON or form data), providing versatile options for different client requirements. [Here](https://github.com/serengil/deepface/tree/master/deepface/api/postman), you can find a postman project to find out how these methods should be called.
**Dockerized Service** - [`Demo`](https://youtu.be/9Tk9lRQareA)

154
deepface/api/postman/deepface-api.postman_collection.json
View File

@ -1,12 +1,54 @@
{
"info": {
"_postman_id": "4c0b144e-4294-4bdd-8072-bcb326b1fed2",
"_postman_id": "26c5ee53-1f4b-41db-9342-3617c90059d3",
"name": "deepface-api",
"schema": "https://schema.getpostman.com/json/collection/v2.1.0/collection.json"
},
"item": [
{
"name": "Represent",
"name": "Represent - form data",
"request": {
"method": "POST",
"header": [],
"body": {
"mode": "formdata",
"formdata": [
{
"key": "img",
"type": "file",
"src": "/Users/sefik/Desktop/deepface/tests/dataset/img1.jpg"
},
{
"key": "model_name",
"value": "Facenet",
"type": "text"
}
],
"options": {
"raw": {
"language": "json"
}
}
},
"url": {
"raw": "http://127.0.0.1:5005/represent",
"protocol": "http",
"host": [
"127",
"0",
"0",
"1"
],
"port": "5005",
"path": [
"represent"
]
}
},
"response": []
},
{
"name": "Represent - default",
"request": {
"method": "POST",
"header": [],
@ -20,7 +62,7 @@
}
},
"url": {
"raw": "http://127.0.0.1:5000/represent",
"raw": "http://127.0.0.1:5005/represent",
"protocol": "http",
"host": [
"127",
@ -28,7 +70,7 @@
"0",
"1"
],
"port": "5000",
"port": "5005",
"path": [
"represent"
]
@ -37,13 +79,13 @@
"response": []
},
{
"name": "Face verification",
"name": "Face verification - default",
"request": {
"method": "POST",
"header": [],
"body": {
"mode": "raw",
"raw": " {\n \t\"img1_path\": \"/Users/sefik/Desktop/deepface/tests/dataset/img1.jpg\",\n \"img2_path\": \"/Users/sefik/Desktop/deepface/tests/dataset/img2.jpg\",\n \"model_name\": \"Facenet\",\n \"detector_backend\": \"mtcnn\",\n \"distance_metric\": \"euclidean\"\n }",
"raw": " {\n \t\"img1\": \"/Users/sefik/Desktop/deepface/tests/dataset/img1.jpg\",\n \"img2\": \"/Users/sefik/Desktop/deepface/tests/dataset/img2.jpg\",\n \"model_name\": \"Facenet\",\n \"detector_backend\": \"mtcnn\",\n \"distance_metric\": \"euclidean\"\n }",
"options": {
"raw": {
"language": "json"
@ -51,7 +93,7 @@
}
},
"url": {
"raw": "http://127.0.0.1:5000/verify",
"raw": "http://127.0.0.1:5005/verify",
"protocol": "http",
"host": [
"127",
@ -59,7 +101,7 @@
"0",
"1"
],
"port": "5000",
"port": "5005",
"path": [
"verify"
]
@ -68,13 +110,29 @@
"response": []
},
{
"name": "Face analysis",
"name": "Face verification - form data",
"request": {
"method": "POST",
"header": [],
"body": {
"mode": "raw",
"raw": "{\n \"img_path\": \"/Users/sefik/Desktop/deepface/tests/dataset/couple.jpg\",\n \"actions\": [\"age\", \"gender\", \"emotion\", \"race\"]\n}",
"mode": "formdata",
"formdata": [
{
"key": "img1",
"type": "file",
"src": "/Users/sefik/Desktop/deepface/tests/dataset/img1.jpg"
},
{
"key": "img2",
"type": "file",
"src": "/Users/sefik/Desktop/deepface/tests/dataset/img2.jpg"
},
{
"key": "model_name",
"value": "Facenet",
"type": "text"
}
],
"options": {
"raw": {
"language": "json"
@ -82,7 +140,7 @@
}
},
"url": {
"raw": "http://127.0.0.1:5000/analyze",
"raw": "http://127.0.0.1:5005/verify",
"protocol": "http",
"host": [
"127",
@ -90,7 +148,77 @@
"0",
"1"
],
"port": "5000",
"port": "5005",
"path": [
"verify"
]
}
},
"response": []
},
{
"name": "Face analysis - default",
"request": {
"method": "POST",
"header": [],
"body": {
"mode": "raw",
"raw": "{\n \"img\": \"/Users/sefik/Desktop/deepface/tests/dataset/img1.jpg\",\n \"actions\": [\"age\", \"gender\", \"emotion\", \"race\"]\n}",
"options": {
"raw": {
"language": "json"
}
}
},
"url": {
"raw": "http://127.0.0.1:5005/analyze",
"protocol": "http",
"host": [
"127",
"0",
"0",
"1"
],
"port": "5005",
"path": [
"analyze"
]
}
},
"response": []
},
{
"name": "Face analysis - form data",
"request": {
"method": "POST",
"header": [],
"body": {
"mode": "formdata",
"formdata": [
{
"key": "img",
"type": "file",
"src": "/Users/sefik/Desktop/deepface/tests/dataset/img1.jpg"
},
{
"key": "actions",
"value": "\"[age, gender]\"",
"type": "text"
}
],
"options": {
"raw": {
"language": "json"
}
}
},
"url": {
"raw": "http://localhost:5005/analyze",
"protocol": "http",
"host": [
"localhost"
],
"port": "5005",
"path": [
"analyze"
]

124
deepface/api/src/modules/core/routes.py
View File

@ -1,31 +1,86 @@
# built-in dependencies
from typing import Union
# 3rd party dependencies
from flask import Blueprint, request
import numpy as np
# project dependencies
from deepface import DeepFace
from deepface.api.src.modules.core import service
from deepface.commons import image_utils
from deepface.commons.logger import Logger
logger = Logger()
blueprint = Blueprint("routes", __name__)
# pylint: disable=no-else-return, broad-except
@blueprint.route("/")
def home():
return f"<h1>Welcome to DeepFace API v{DeepFace.__version__}!</h1>"
def extract_image_from_request(img_key: str) -> Union[str, np.ndarray]:
"""
Extracts an image from the request either from json or a multipart/form-data file.
Args:
img_key (str): The key used to retrieve the image data
from the request (e.g., 'img1').
Returns:
img (str or np.ndarray): Given image detail (base64 encoded string, image path or url)
or the decoded image as a numpy array.
"""
# Check if the request is multipart/form-data (file input)
if request.files:
# request.files is instance of werkzeug.datastructures.ImmutableMultiDict
# file is instance of werkzeug.datastructures.FileStorage
file = request.files.get(img_key)
if file is None:
raise ValueError(f"Request form data doesn't have {img_key}")
if file.filename == "":
raise ValueError(f"No file uploaded for '{img_key}'")
img = image_utils.load_image_from_file_storage(file)
return img
# Check if the request is coming as base64, file path or url from json or form data
elif request.is_json or request.form:
input_args = request.get_json() or request.form.to_dict()
if input_args is None:
raise ValueError("empty input set passed")
# this can be base64 encoded image, and image path or url
img = input_args.get(img_key)
if not img:
raise ValueError(f"'{img_key}' not found in either json or form data request")
return img
# If neither JSON nor file input is present
raise ValueError(f"'{img_key}' not found in request in either json or form data")
@blueprint.route("/represent", methods=["POST"])
def represent():
input_args = request.get_json()
input_args = request.get_json() or request.form.to_dict()
if input_args is None:
return {"message": "empty input set passed"}
img_path = input_args.get("img") or input_args.get("img_path")
if img_path is None:
return {"message": "you must pass img_path input"}
try:
img = extract_image_from_request("img")
except Exception as err:
return {"exception": str(err)}, 400
obj = service.represent(
img_path=img_path,
img_path=img,
model_name=input_args.get("model_name", "VGG-Face"),
detector_backend=input_args.get("detector_backend", "opencv"),
enforce_detection=input_args.get("enforce_detection", True),
@ -41,23 +96,21 @@ def represent():
@blueprint.route("/verify", methods=["POST"])
def verify():
input_args = request.get_json()
input_args = request.get_json() or request.form.to_dict()
if input_args is None:
return {"message": "empty input set passed"}
try:
img1 = extract_image_from_request("img1")
except Exception as err:
return {"exception": str(err)}, 400
img1_path = input_args.get("img1") or input_args.get("img1_path")
img2_path = input_args.get("img2") or input_args.get("img2_path")
if img1_path is None:
return {"message": "you must pass img1_path input"}
if img2_path is None:
return {"message": "you must pass img2_path input"}
try:
img2 = extract_image_from_request("img2")
except Exception as err:
return {"exception": str(err)}, 400
verification = service.verify(
img1_path=img1_path,
img2_path=img2_path,
img1_path=img1,
img2_path=img2,
model_name=input_args.get("model_name", "VGG-Face"),
detector_backend=input_args.get("detector_backend", "opencv"),
distance_metric=input_args.get("distance_metric", "cosine"),
@ -73,18 +126,31 @@ def verify():
@blueprint.route("/analyze", methods=["POST"])
def analyze():
input_args = request.get_json()
input_args = request.get_json() or request.form.to_dict()
if input_args is None:
return {"message": "empty input set passed"}
try:
img = extract_image_from_request("img")
except Exception as err:
return {"exception": str(err)}, 400
img_path = input_args.get("img") or input_args.get("img_path")
if img_path is None:
return {"message": "you must pass img_path input"}
actions = input_args.get("actions", ["age", "gender", "emotion", "race"])
# actions is the only argument instance of list or tuple
# if request is form data, input args can either be text or file
if isinstance(actions, str):
actions = (
actions.replace("[", "")
.replace("]", "")
.replace("(", "")
.replace(")", "")
.replace('"', "")
.replace("'", "")
.replace(" ", "")
.split(",")
)
demographies = service.analyze(
img_path=img_path,
actions=input_args.get("actions", ["age", "gender", "emotion", "race"]),
img_path=img,
actions=actions,
detector_backend=input_args.get("detector_backend", "opencv"),
enforce_detection=input_args.get("enforce_detection", True),
align=input_args.get("align", True),

23
deepface/api/src/modules/core/service.py
View File

@ -1,15 +1,22 @@
# built-in dependencies
import traceback
from typing import Optional
from typing import Optional, Union
# 3rd party dependencies
import numpy as np
# project dependencies
from deepface import DeepFace
from deepface.commons.logger import Logger
logger = Logger()
# pylint: disable=broad-except
def represent(
img_path: str,
img_path: Union[str, np.ndarray],
model_name: str,
detector_backend: str,
enforce_detection: bool,
@ -32,12 +39,14 @@ def represent(
return result
except Exception as err:
tb_str = traceback.format_exc()
logger.error(str(err))
logger.error(tb_str)
return {"error": f"Exception while representing: {str(err)} - {tb_str}"}, 400
def verify(
img1_path: str,
img2_path: str,
img1_path: Union[str, np.ndarray],
img2_path: Union[str, np.ndarray],
model_name: str,
detector_backend: str,
distance_metric: str,
@ -59,11 +68,13 @@ def verify(
return obj
except Exception as err:
tb_str = traceback.format_exc()
logger.error(str(err))
logger.error(tb_str)
return {"error": f"Exception while verifying: {str(err)} - {tb_str}"}, 400
def analyze(
img_path: str,
img_path: Union[str, np.ndarray],
actions: list,
detector_backend: str,
enforce_detection: bool,
@ -85,4 +96,6 @@ def analyze(
return result
except Exception as err:
tb_str = traceback.format_exc()
logger.error(str(err))
logger.error(tb_str)
return {"error": f"Exception while analyzing: {str(err)} - {tb_str}"}, 400

16
deepface/commons/image_utils.py
View File

@ -11,6 +11,7 @@ import requests
import numpy as np
import cv2
from PIL import Image
from werkzeug.datastructures import FileStorage
def list_images(path: str) -> List[str]:
@ -133,6 +134,21 @@ def load_image_from_base64(uri: str) -> np.ndarray:
return img_bgr
def load_image_from_file_storage(file: FileStorage) -> np.ndarray:
"""
Loads an image from a FileStorage object and decodes it into an OpenCV image.
Args:
file (FileStorage): The FileStorage object containing the image file.
Returns:
img (np.ndarray): The decoded image as a numpy array (OpenCV format).
"""
file_bytes = np.frombuffer(file.read(), np.uint8)
image = cv2.imdecode(file_bytes, cv2.IMREAD_COLOR)
if image is None:
raise ValueError("Failed to decode image")
return image
def load_image_from_web(url: str) -> np.ndarray:
"""
Loading an image from web

2
requirements_local
View File

@ -3,4 +3,4 @@ pandas==2.0.3
Pillow==9.0.0
opencv-python==4.9.0.80
tensorflow==2.13.1
keras==2.13.1
keras==2.13.1

160
tests/test_api.py
View File

@ -1,16 +1,29 @@
# built-in dependencies
import os
import base64
import unittest
# 3rd party dependencies
import gdown
# project dependencies
from deepface.api.src.app import create_app
from deepface.commons.logger import Logger
logger = Logger()
IMG1_SOURCE = (
"https://raw.githubusercontent.com/serengil/deepface/refs/heads/master/tests/dataset/img1.jpg"
)
IMG2_SOURCE = (
"https://raw.githubusercontent.com/serengil/deepface/refs/heads/master/tests/dataset/img2.jpg"
)
class TestVerifyEndpoint(unittest.TestCase):
def setUp(self):
download_test_images(IMG1_SOURCE)
download_test_images(IMG2_SOURCE)
app = create_app()
app.config["DEBUG"] = True
app.config["TESTING"] = True
@ -18,8 +31,8 @@ class TestVerifyEndpoint(unittest.TestCase):
def test_tp_verify(self):
data = {
"img1_path": "dataset/img1.jpg",
"img2_path": "dataset/img2.jpg",
"img1": "dataset/img1.jpg",
"img2": "dataset/img2.jpg",
}
response = self.app.post("/verify", json=data)
assert response.status_code == 200
@ -40,8 +53,8 @@ class TestVerifyEndpoint(unittest.TestCase):
def test_tn_verify(self):
data = {
"img1_path": "dataset/img1.jpg",
"img2_path": "dataset/img2.jpg",
"img1": "dataset/img1.jpg",
"img2": "dataset/img2.jpg",
}
response = self.app.post("/verify", json=data)
assert response.status_code == 200
@ -83,14 +96,11 @@ class TestVerifyEndpoint(unittest.TestCase):
def test_represent_encoded(self):
image_path = "dataset/img1.jpg"
with open(image_path, "rb") as image_file:
encoded_string = "data:image/jpeg;base64," + \
base64.b64encode(image_file.read()).decode("utf8")
encoded_string = "data:image/jpeg;base64," + base64.b64encode(image_file.read()).decode(
"utf8"
)
data = {
"model_name": "Facenet",
"detector_backend": "mtcnn",
"img": encoded_string
}
data = {"model_name": "Facenet", "detector_backend": "mtcnn", "img": encoded_string}
response = self.app.post("/represent", json=data)
assert response.status_code == 200
@ -112,7 +122,7 @@ class TestVerifyEndpoint(unittest.TestCase):
data = {
"model_name": "Facenet",
"detector_backend": "mtcnn",
"img": "https://github.com/serengil/deepface/blob/master/tests/dataset/couple.jpg?raw=true"
"img": "https://github.com/serengil/deepface/blob/master/tests/dataset/couple.jpg?raw=true",
}
response = self.app.post("/represent", json=data)
@ -155,8 +165,9 @@ class TestVerifyEndpoint(unittest.TestCase):
def test_analyze_inputformats(self):
image_path = "dataset/couple.jpg"
with open(image_path, "rb") as image_file:
encoded_image = "data:image/jpeg;base64," + \
base64.b64encode(image_file.read()).decode("utf8")
encoded_image = "data:image/jpeg;base64," + base64.b64encode(image_file.read()).decode(
"utf8"
)
image_sources = [
# image path
@ -164,7 +175,7 @@ class TestVerifyEndpoint(unittest.TestCase):
# image url
f"https://github.com/serengil/deepface/blob/master/tests/{image_path}?raw=true",
# encoded image
encoded_image
encoded_image,
]
results = []
@ -189,25 +200,38 @@ class TestVerifyEndpoint(unittest.TestCase):
assert i.get("dominant_emotion") is not None
assert i.get("dominant_race") is not None
assert len(results[0]["results"]) == len(results[1]["results"])\
and len(results[0]["results"]) == len(results[2]["results"])
assert len(results[0]["results"]) == len(results[1]["results"]) and len(
results[0]["results"]
) == len(results[2]["results"])
for i in range(len(results[0]['results'])):
assert results[0]["results"][i]["dominant_emotion"] == results[1]["results"][i]["dominant_emotion"]\
and results[0]["results"][i]["dominant_emotion"] == results[2]["results"][i]["dominant_emotion"]
for i in range(len(results[0]["results"])):
assert (
results[0]["results"][i]["dominant_emotion"]
== results[1]["results"][i]["dominant_emotion"]
and results[0]["results"][i]["dominant_emotion"]
== results[2]["results"][i]["dominant_emotion"]
)
assert results[0]["results"][i]["dominant_gender"] == results[1]["results"][i]["dominant_gender"]\
and results[0]["results"][i]["dominant_gender"] == results[2]["results"][i]["dominant_gender"]
assert (
results[0]["results"][i]["dominant_gender"]
== results[1]["results"][i]["dominant_gender"]
and results[0]["results"][i]["dominant_gender"]
== results[2]["results"][i]["dominant_gender"]
)
assert results[0]["results"][i]["dominant_race"] == results[1]["results"][i]["dominant_race"]\
and results[0]["results"][i]["dominant_race"] == results[2]["results"][i]["dominant_race"]
assert (
results[0]["results"][i]["dominant_race"]
== results[1]["results"][i]["dominant_race"]
and results[0]["results"][i]["dominant_race"]
== results[2]["results"][i]["dominant_race"]
)
logger.info("✅ different inputs test is done")
def test_invalid_verify(self):
data = {
"img1_path": "dataset/invalid_1.jpg",
"img2_path": "dataset/invalid_2.jpg",
"img1": "dataset/invalid_1.jpg",
"img2": "dataset/invalid_2.jpg",
}
response = self.app.post("/verify", json=data)
assert response.status_code == 400
@ -227,3 +251,87 @@ class TestVerifyEndpoint(unittest.TestCase):
}
response = self.app.post("/analyze", json=data)
assert response.status_code == 400
def test_analyze_for_multipart_form_data(self):
with open("/tmp/img1.jpg", "rb") as img_file:
response = self.app.post(
"/analyze",
content_type="multipart/form-data",
data={
"img": (img_file, "test_image.jpg"),
"actions": '["age", "gender"]',
"detector_backend": "mtcnn",
},
)
assert response.status_code == 200
result = response.json
assert isinstance(result, dict)
assert result.get("age") is not True
assert result.get("dominant_gender") is not True
logger.info("✅ analyze api for multipart form data test is done")
def test_verify_for_multipart_form_data(self):
with open("/tmp/img1.jpg", "rb") as img1_file:
with open("/tmp/img2.jpg", "rb") as img2_file:
response = self.app.post(
"/verify",
content_type="multipart/form-data",
data={
"img1": (img1_file, "first_image.jpg"),
"img2": (img2_file, "second_image.jpg"),
"model_name": "Facenet",
"detector_backend": "mtcnn",
"distance_metric": "euclidean",
},
)
assert response.status_code == 200
result = response.json
assert isinstance(result, dict)
assert result.get("verified") is not None
assert result.get("model") == "Facenet"
assert result.get("similarity_metric") is not None
assert result.get("detector_backend") == "mtcnn"
assert result.get("threshold") is not None
assert result.get("facial_areas") is not None
logger.info("✅ verify api for multipart form data test is done")
def test_represent_for_multipart_form_data(self):
with open("/tmp/img1.jpg", "rb") as img_file:
response = self.app.post(
"/represent",
content_type="multipart/form-data",
data={
"img": (img_file, "first_image.jpg"),
"model_name": "Facenet",
"detector_backend": "mtcnn",
},
)
assert response.status_code == 200
result = response.json
assert isinstance(result, dict)
logger.info("✅ represent api for multipart form data test is done")
def test_represent_for_multipart_form_data_and_filepath(self):
response = self.app.post(
"/represent",
content_type="multipart/form-data",
data={
"img": "/tmp/img1.jpg",
"model_name": "Facenet",
"detector_backend": "mtcnn",
},
)
assert response.status_code == 200
result = response.json
assert isinstance(result, dict)
logger.info("✅ represent api for multipart form data and file path test is done")
def download_test_images(url: str):
file_name = url.split("/")[-1]
target_file = f"/tmp/{file_name}"
if os.path.exists(target_file) is True:
return
gdown.download(url, target_file, quiet=False)