Update app.py

app.py

@@ -21,11 +21,8 @@ except (ImportError, AttributeError):
     face_mesh = None
 
 # --- Helper Functions ---
-
 def get_landmarks(img, landmark_step=1):
-    if img is None:
-        return None
-    if face_mesh is None:
+    if img is None or face_mesh is None:
         return None
     img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
     try:
@@ -36,132 +33,115 @@ def get_landmarks(img, landmark_step=1):
         return None
     landmarks_mp = results.multi_face_landmarks[0]
     h, w, _ = img.shape
-    full_landmarks = np.array([(pt.x * w, pt.y * h) for pt in landmarks_mp.landmark], dtype=np.float32)
-    landmarks = full_landmarks[::landmark_step] if landmark_step > 1 else full_landmarks
+    pts = np.array([(pt.x * w, pt.y * h) for pt in landmarks_mp.landmark], dtype=np.float32)
+    landmarks = pts[::landmark_step] if landmark_step > 1 else pts
     if not np.all(np.isfinite(landmarks)):
         return None
-    corners = np.array([[0, 0], [w - 1, 0], [0, h - 1], [w - 1, h - 1]], dtype=np.float32)
+    corners = np.array([[0,0],[w-1,0],[0,h-1],[w-1,h-1]], dtype=np.float32)
     return np.vstack((landmarks, corners))
 
-
 def calculate_delaunay_triangles(rect, points):
-    if points is None or len(points) < 3:
+    if points is None or len(points)<3:
         return []
-    points[:, 0] = np.clip(points[:, 0], rect[0], rect[0] + rect[2] - 1)
-    points[:, 1] = np.clip(points[:, 1], rect[1], rect[1] + rect[3] - 1)
+    points[:,0] = np.clip(points[:,0], rect[0], rect[0]+rect[2]-1)
+    points[:,1] = np.clip(points[:,1], rect[1], rect[1]+rect[3]-1)
     subdiv = cv2.Subdiv2D(rect)
     inserted = {}
-    for i, p in enumerate(points):
-        tup = (int(p[0]), int(p[1]))
-        if tup not in inserted:
+    for i,p in enumerate(points):
+        key = (int(p[0]), int(p[1]))
+        if key not in inserted:
             try:
-                subdiv.insert(tup)
-                inserted[tup] = i
+                subdiv.insert(key)
+                inserted[key]=i
             except cv2.error:
                 continue
-    triangles = subdiv.getTriangleList()
-    delaunay = []
-    for t in triangles:
-        coords = [(int(t[0]), int(t[1])), (int(t[2]), int(t[3])), (int(t[4]), int(t[5]))]
-        if all(rect[0] <= x < rect[0] + rect[2] and rect[1] <= y < rect[1] + rect[3] for x, y in coords):
-            idxs = [inserted.get(c) for c in coords]
-            if all(i is not None for i in idxs) and len(set(idxs)) == 3:
+    tris = subdiv.getTriangleList()
+    delaunay=[]
+    for t in tris:
+        coords=[(int(t[0]),int(t[1])),(int(t[2]),int(t[3])),(int(t[4]),int(t[5]))]
+        if all(rect[0]<=x<rect[0]+rect[2] and rect[1]<=y<rect[1]+rect[3] for x,y in coords):
+            idxs=[inserted.get(c) for c in coords]
+            if all(i is not None for i in idxs) and len(set(idxs))==3:
                 delaunay.append(idxs)
     return delaunay
 
-
-def warp_triangle(img1, img2, t1, t2):
-    if len(t1) != 3 or len(t2) != 3:
+def warp_triangle(img1,img2,t1,t2):
+    if len(t1)!=3 or len(t2)!=3:
         return
-    r1 = cv2.boundingRect(np.float32([t1]))
-    r2 = cv2.boundingRect(np.float32([t2]))
-    if r1[2] == 0 or r1[3] == 0 or r2[2] == 0 or r2[3] == 0:
+    r1=cv2.boundingRect(np.float32([t1])); r2=cv2.boundingRect(np.float32([t2]))
+    if r1[2]==0 or r1[3]==0 or r2[2]==0 or r2[3]==0:
         return
-    t1_rect = [(t1[i][0] - r1[0], t1[i][1] - r1[1]) for i in range(3)]
-    t2_rect = [(t2[i][0] - r2[0], t2[i][1] - r2[1]) for i in range(3)]
-    mask = np.zeros((r2[3], r2[2], 3), dtype=np.float32)
-    cv2.fillConvexPoly(mask, np.int32(t2_rect), (1.0, 1.0, 1.0), 16, 0)
-    img1_rect = img1[r1[1]:r1[1]+r1[3], r1[0]:r1[0]+r1[2]]
-    if img1_rect.size == 0:
-        return
-    warp_mat = cv2.getAffineTransform(np.float32(t1_rect), np.float32(t2_rect))
-    img2_rect = cv2.warpAffine(img1_rect, warp_mat, (r2[2], r2[3]), flags=cv2.INTER_LINEAR, borderMode=cv2.BORDER_REFLECT_101)
-    img2_rect *= mask
-    y1, y2 = r2[1], r2[1] + r2[3]
-    x1, x2 = r2[0], r2[0] + r2[2]
-    img2[y1:y2, x1:x2] = img2[y1:y2, x1:x2] * (1 - mask) + img2_rect
-
+    t1r=[(t1[i][0]-r1[0],t1[i][1]-r1[1]) for i in range(3)]
+    t2r=[(t2[i][0]-r2[0],t2[i][1]-r2[1]) for i in range(3)]
+    mask=np.zeros((r2[3],r2[2],3),dtype=np.float32)
+    cv2.fillConvexPoly(mask,np.int32(t2r),(1,1,1),16)
+    src=img1[r1[1]:r1[1]+r1[3],r1[0]:r1[0]+r1[2]]
+    M=cv2.getAffineTransform(np.float32(t1r),np.float32(t2r))
+    warped=cv2.warpAffine(src,M,(r2[2],r2[3]),flags=cv2.INTER_LINEAR,borderMode=cv2.BORDER_REFLECT_101)
+    warped*=mask
+    y1,y2=r2[1],r2[1]+r2[3]; x1,x2=r2[0],r2[0]+r2[2]
+    img2[y1:y2,x1:x2]=img2[y1:y2,x1:x2]*(1-mask)+warped
 
-def morph_faces(img1_orig, img2_orig, alpha, resize_dim, landmark_step):
-    if img1_orig is None or img2_orig is None:
-        return np.zeros((resize_dim, resize_dim, 3), dtype=np.uint8)
-    img1 = cv2.resize(img1_orig, (resize_dim, resize_dim))
-    img2 = cv2.resize(img2_orig, (resize_dim, resize_dim))
-    landmarks1 = get_landmarks(img1, landmark_step)
-    landmarks2 = get_landmarks(img2, landmark_step)
-    if landmarks1 is None or landmarks2 is None or landmarks1.shape != landmarks2.shape:
-        return cv2.addWeighted(img1, 1-alpha, img2, alpha, 0)
-    morphed_pts = (1-alpha)*landmarks1 + alpha*landmarks2
-    rect = (0, 0, resize_dim, resize_dim)
-    tris = calculate_delaunay_triangles(rect, morphed_pts)
+def morph_faces(img1, img2, alpha, dim, step):
+    if img1 is None or img2 is None:
+        return np.zeros((dim,dim,3),dtype=np.uint8)
+    a=cv2.resize(img1,(dim,dim)); b=cv2.resize(img2,(dim,dim))
+    l1=get_landmarks(a,step); l2=get_landmarks(b,step)
+    if l1 is None or l2 is None or l1.shape!=l2.shape:
+        return cv2.addWeighted(a,1-alpha,b,alpha,0)
+    m=(1-alpha)*l1+alpha*l2
+    tris=calculate_delaunay_triangles((0,0,dim,dim),m)
     if not tris:
-        return cv2.addWeighted(img1, 1-alpha, img2, alpha, 0)
-    img1_f = img1.astype(np.float32)/255.0
-    img2_f = img2.astype(np.float32)/255.0
-    w1 = np.zeros_like(img1_f)
-    w2 = np.zeros_like(img2_f)
+        return cv2.addWeighted(a,1-alpha,b,alpha,0)
+    A=a.astype(np.float32)/255; B=b.astype(np.float32)/255
+    Wa=np.zeros_like(A); Wb=np.zeros_like(B)
     for ids in tris:
-        t1 = landmarks1[ids]; t2 = landmarks2[ids]; tm = morphed_pts[ids]
-        warp_triangle(img1_f, w1, t1, tm)
-        warp_triangle(img2_f, w2, t2, tm)
-    morph = (1-alpha)*w1 + alpha*w2
-    return (morph*255).astype(np.uint8)
+        warp_triangle(A,Wa,l1[ids],m[ids]); warp_triangle(B,Wb,l2[ids],m[ids])
+    out=(1-alpha)*Wa+alpha*Wb
+    return (out*255).astype(np.uint8)
 
-
-def process_video(video_path, target_img, transition_level, resolution, landmark_sampling):
+def process_video(video_path, target_img, trans, res, step, progress=gr.Progress()):
     if video_path is None or target_img is None:
-        dummy = tempfile.NamedTemporaryFile(delete=False, suffix=".mp4").name
-        out = cv2.VideoWriter(dummy, cv2.VideoWriter_fourcc(*'mp4v'), 24, (resolution, resolution))
-        out.release()
-        return dummy
-    target_bgr = cv2.cvtColor(target_img, cv2.COLOR_RGB2BGR)
-    alpha = float(np.clip((transition_level+1)/2,0,1))
-    cap = cv2.VideoCapture(video_path)
-    fps = cap.get(cv2.CAP_PROP_FPS) or 24
-    out_file = tempfile.NamedTemporaryFile(delete=False, suffix=".mp4").name
-    out = cv2.VideoWriter(out_file, cv2.VideoWriter_fourcc(*'mp4v'), fps, (resolution, resolution))
+        tmp=tempfile.NamedTemporaryFile(delete=False,suffix='.mp4').name
+        cv2.VideoWriter(tmp,cv2.VideoWriter_fourcc(*'mp4v'),24,(res,res)).release();return tmp
+    tgt=cv2.cvtColor(target_img,cv2.COLOR_RGB2BGR)
+    alpha=float(np.clip((trans+1)/2,0,1))
+    cap=cv2.VideoCapture(video_path)
+    n=int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
+    fps=cap.get(cv2.CAP_PROP_FPS) or 24
+    tmp=tempfile.NamedTemporaryFile(delete=False,suffix='.mp4').name
+    out=cv2.VideoWriter(tmp,cv2.VideoWriter_fourcc(*'mp4v'),fps,(res,res))
+    i=0
     while True:
-        ret, frame = cap.read()
+        ret,frame=cap.read()
         if not ret: break
-        mor = morph_faces(frame, target_bgr, alpha, resolution, landmark_sampling)
+        i+=1
+        progress(i/n,desc=f'Frame {i}/{n}')
+        mor=morph_faces(frame,tgt,alpha,res,step)
         out.write(mor)
-    cap.release(); out.release()
-    return out_file
+    cap.release();out.release();progress(1,desc='Done')
+    return tmp
 
 # --- Gradio App ---
-css = """video, img { object-fit: contain !important; }"""
+css="""video, img{object-fit:contain!important;}"""
 with gr.Blocks(css=css) as iface:
     gr.Markdown("# Real-Time Video Face Morph 🚀")
-    gr.Markdown("Use the button below to generate and show a progress bar during processing.")
+    gr.Markdown("Click 'Generate Morph' and watch the progress bar during processing.")
     with gr.Row():
-        video_input = gr.Video(label="Input Video")
-        img_input = gr.Image(type="numpy", label="Target Face Image")
+        vid=gr.Video(label='Input Video')
+        img=gr.Image(type='numpy',label='Target Face Image')
     with gr.Row():
-        resolution_slider = gr.Dropdown([256,384,512,768], value=512, label="Resolution")
-        landmark_slider = gr.Slider(1,4,value=1,step=1, label="Landmark Sub-sampling")
-    transition_slider = gr.Slider(-1.0,1.0,value=0.0,step=0.05, label="Transition Level")
-    generate_btn = gr.Button("Generate Morph 🚀", variant="primary")
-    progress_bar = gr.Progress()
-    video_output = gr.Video(label="Morphed Video")
-    
-    generate_btn.click(
+        res=gr.Dropdown([256,384,512,768],value=512,label='Resolution')
+        step=gr.Slider(1,4,value=1,step=1,label='Landmark Sub-sampling')
+    trans=gr.Slider(-1,1,value=0,step=0.05,label='Transition Level')
+    btn=gr.Button('Generate Morph 🚀',variant='primary')
+    prog=gr.Progress()
+    out=gr.Video(label='Morphed Video')
+    btn.click(
         fn=process_video,
-        inputs=[video_input, img_input, transition_slider, resolution_slider, landmark_slider],
-        outputs=video_output,
-        show_progress=True
+        inputs=[vid,img,trans,res,step],
+        outputs=out,
+        progress=prog
     )
-    
     gr.Markdown("---\n*Built with Gradio, OpenCV & MediaPipe.*")
-
-if __name__ == "__main__":
-    iface.launch(debug=True)
+if __name__=='__main__': iface.launch(debug=True)