Delete utils.py

utils.py

@@ -1,116 +0,0 @@
-import base64
-import os
-import requests
-
-import cv2
-import numpy as np
-from PIL import Image
-
-from .exceptions import InvalidImage
-from .emotionsmultilanguage import emotions_dict
-
-
-def draw_annotations(
-    frame: np.ndarray,
-    faces: list,
-    boxes=True,
-    scores=True,
-    color: tuple = (0, 155, 255),
-    lang: str = "en",
-    size_multiplier: int = 1,
-) -> np.ndarray:
-    """Draws boxes around detected faces. Faces is a list of dicts with `box` and `emotions`."""
-    if not len(faces):
-        return frame
-
-    for face in faces:
-        x, y, w, h = face["box"]
-        emotions = face["emotions"]
-
-        if boxes:
-            cv2.rectangle(
-                frame,
-                (x, y, w, h),
-                color,
-                2,
-            )
-
-        if scores:
-            frame = draw_scores(frame, emotions, (x, y, w, h), lang, size_multiplier)
-    return frame
-
-
-def loadBase64Img(uri):
-    encoded_data = uri.split(",")[1]
-    nparr = np.fromstring(base64.b64decode(encoded_data), np.uint8)
-    img = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
-    return img
-
-
-def pil_to_bgr(pil_image):
-    return cv2.cvtColor(np.array(pil_image), cv2.COLOR_RGB2BGR)
-
-
-def load_image(img):
-    """Modified from github.com/serengil/deepface. Returns bgr (opencv-style) numpy array."""
-    is_exact_image = is_base64_img = is_url_img = False
-
-    if type(img).__module__ == np.__name__:
-        is_exact_image = True
-    elif img is None:
-        raise InvalidImage("Image not valid.")
-    elif len(img) > 11 and img[0:11] == "data:image/":
-        is_base64_img = True
-    elif len(img) > 11 and img.startswith("http"):
-        is_url_img = True
-
-    if is_base64_img:
-        img = loadBase64Img(img)
-    elif is_url_img:
-        img = pil_to_bgr(Image.open(requests.get(img, stream=True).raw))
-    elif not is_exact_image:  # image path passed as input
-        if not os.path.isfile(img):
-            raise ValueError(f"Confirm that {img} exists")
-        img = cv2.imread(img)
-
-    if img is None or not hasattr(img, "shape"):
-        raise InvalidImage("Image not valid.")
-
-    return img
-
-
-def draw_scores(
-    frame: np.ndarray,
-    emotions: dict,
-    bounding_box: dict,
-    lang: str = "en",
-    size_multiplier: int = 1,
-) -> np.ndarray:
-    """Draw scores for each emotion under faces."""
-    GRAY = (211, 211, 211)
-    GREEN = (0, 255, 0)
-    x, y, w, h = bounding_box
-
-    for idx, (emotion, score) in enumerate(emotions.items()):
-        color = GRAY if score < 0.01 else GREEN
-
-        if lang != "en":
-            emotion = emotions_dict[emotion][lang]
-
-        emotion_score = "{}: {}".format(
-            emotion, "{:.2f}".format(score) if score >= 0.01 else ""
-        )
-        cv2.putText(
-            frame,
-            emotion_score,
-            (
-                x,
-                y + h + (15 * size_multiplier) + idx * (15 * size_multiplier),
-            ),
-            cv2.FONT_HERSHEY_SIMPLEX,
-            0.5 * size_multiplier,
-            color,
-            1 * size_multiplier,
-            cv2.LINE_AA,
-        )
-    return frame