matitos_news/app_cv/Demo.ipynb

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import base64
import json
import requests
import io
import numpy as np
import PIL.Image
import cv2
from pprint import pprint

def process_image(path_img):
    with open(path_img, "rb") as image_file:
        encoded_string = base64.b64encode(image_file.read()).decode('utf-8')
    response = requests.post(
        'http://localhost:5000/process',
        headers={'Content-Type': 'application/json'},
        data=json.dumps({'image': encoded_string})
    )
    response_dict = response.json()
    pprint(response_dict)
    # Decode
    image_bytes = base64.b64decode(response_dict.get("image_b64"))
    img_array = np.frombuffer(io.BytesIO(image_bytes).getvalue(), dtype=np.uint8)
    img_bgr = cv2.imdecode(img_array, cv2.IMREAD_COLOR)
    img_rgb = img_bgr[:, :, ::-1]
    return img_rgb

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path_img = "imgs/img_1p.jpg"
PIL.Image.fromarray( process_image(path_img) )

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path_img = "imgs/img_nude.jpg"
PIL.Image.fromarray( process_image(path_img) )

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'''
# !git clone https://github.com/wildchlamydia/mivolo
# !pip install ultralytics yt_dlp pandas scipy timm==0.8.13.dev0
# !pip install ./mivolo

!python mivolo/demo.py \
    --input "face_data/sample_image.jpg" \
    --output "output" \
    --detector-weights "mivolo/pretrained/yolov8x_person_face.pt" \
    --checkpoint "mivolo/pretrained/model_imdb_cross_person_4.22_99.46.pth.tar" \
    --device "cpu" \
    --draw
'''

'''
# !git clone https://github.com/Kartik-3004/facexformer.git
# !pip install huggingface_hub torch torchvision torchaudio opencv-python facenet_pytorch
from huggingface_hub import hf_hub_download
hf_hub_download(repo_id="kartiknarayan/facexformer", filename="ckpts/model.pt", local_dir="./facexformer")

!python facexformer/inference.py \
    --model_path facexformer/ckpts/model.pt \
    --image_path face_data/sample_image.jpg \
    --results_path face_data \
    --task parsing
    x
!python facexformer/inference.py \
    --model_path facexformer/ckpts/model.pt \
    --image_path face_data/face.png \
    --results_path face_data \
    --task landmarks

!python facexformer/inference.py \
    --model_path facexformer/ckpts/model.pt \
    --image_path face_data/face.png \
    --results_path face_data \
    --task headpose

!python facexformer/inference.py \
    --model_path facexformer/ckpts/model.pt \
    --image_path face_data/face.png \
    --results_path face_data \
    --task attributes

!python facexformer/inference.py \
    --model_path facexformer/ckpts/model.pt \
    --image_path face_data/face.png \
    --results_path face_data \
    --task age_gender_race
'''