improve copy image code

app.py

@@ -14,8 +14,10 @@ import numpy as np
 
 from glibvision.cv2_utils import pil_to_bgr_image,bgr_to_rgb
 from gradio_utils import save_image,save_buffer,clear_old_files ,read_file
-from close_eyes import process_close_eyes_image
-from open_mouth import process_open_mouth
+from close_eyes import process_close_eyes_image # little bit better
+from open_mouth import process_open_mouth # I'm truly sorry, but I must admit the code is very confusing.comment still written in Japanese
+
+
 '''
 Face landmark detection based Face Detection.
 https://ai.google.dev/edge/mediapipe/solutions/vision/face_landmarker

demo_header.html

@@ -9,7 +9,8 @@
             This Space use <a href="http://www.apache.org/licenses/LICENSE-2.0">the Apache 2.0</a> Licensed <a href="https://ai.google.dev/edge/mediapipe/solutions/vision/face_landmarker">Mediapipe FaceLandmarker</a> <br>
             One of json format is from MIT licensed <a href="https://github.com/ageitgey/face_recognition">face_recognition</a><br>
             I should clarify because it is confusing: I'm not using dlib's non-MIT licensed 68-point model at all.<br>
-            This is 10-year-old technology. However, most amazing talk-head models,.<br> while often having their core code under MIT/Apache licenses, rely on datasets or NVIDIA libraries with more restrictive licenses.
+            This is 10-year-old technology. However, most amazing talk-head models,<br> while often having their core code under MIT/Apache licenses, rely on datasets or NVIDIA libraries with more restrictive licenses.<br>
+            <a href="https://huggingface.co/blog/Akjava/result-guide-image-eyes-mouth">[Article]</a>Results: Converted Guide Images(eyes-closed and mouth-opened) with Flux.1 schenll img2img/inpaint
         </p>
     </div>
     

lip_utils.py

@@ -541,8 +541,43 @@ def create_rgb(width,height):
 def create_gray(width,height):
     return np.zeros((height, width), dtype=np.uint8)
 
-def copy_image(img1,img2,x,y):
-    img1[y:y+img2.shape[0], x:x+img2.shape[1]] = img2
+
+def copy_image(img1, img2, x, y):
+    """
+    Paste img2 onto img1 at position (x, y).
+    If img2 extends beyond the bounds of img1, only the overlapping part is pasted.
+
+    Parameters:
+    img1 (numpy.ndarray): The base image to modify (H, W, C).
+    img2 (numpy.ndarray): The image to paste onto img1 (h, w, C).
+    x (int): The x-coordinate where img2 will be placed.
+    y (int): The y-coordinate where img2 will be placed.
+
+    Raises:
+    TypeError: If img1 or img2 are not NumPy arrays.
+    ValueError: If x or y are out of bounds of img1.
+    ValueError: If img1 and img2 do not have the same number of channels or are not 3-dimensional arrays.
+    """
+    # Type check
+    if not isinstance(img1, np.ndarray) or not isinstance(img2, np.ndarray):
+        raise TypeError("img1 and img2 must be NumPy arrays.")
+
+    # Channel count check
+    if img1.ndim != 3 or img2.ndim != 3 or img1.shape[2] != img2.shape[2]:
+        raise ValueError("img1 and img2 must have the same number of channels and be 3-dimensional arrays.")
+
+    # Bounds check
+    max_y, max_x, _ = img1.shape
+    if not (0 <= y < max_y and 0 <= x < max_x):
+        raise ValueError(f"x ({x}) and y ({y}) must be within the bounds of img1 ({max_x}, {max_y}).")
+
+    # Calculate the height and width of the overlapping part
+    h = min(img2.shape[0], max_y - y)
+    w = min(img2.shape[1], max_x - x)
+
+    # Paste the overlapping part
+    img1[y:y+h, x:x+w] = img2[:h, :w]
+
 
 def copy_color(img1,x,y,x2,y2,color):
     color_img = np.full((y2-y, x2-x, 4), color, dtype=np.uint8)

open_mouth.py

@@ -1,3 +1,7 @@
+
+#I'm truly sorry, but I must admit the code is very confusing. comment still written in Japanese
+
+
 """
 # Currently on hold,Verifying whether to use other technologies.
 # this is temporaly fixed for work huggingface space