init

app.py

@@ -118,13 +118,13 @@ def compress_UUID():
 
 def run(
         image,
-        mask,
+        landmarks_str : str,
         model,
         opt,
         detector,
         predictor,
         modnet : ModNet,
-) -> tuple[PIL.Image.Image,PIL.Image.Image]:
+) -> tuple[PIL.Image.Image]:
 
     dataroot = 'images/' + compress_UUID()
     opt.dataroot = os.path.join(dataroot, 'src/')
@@ -151,8 +151,26 @@ def run(
     imgfile = os.path.join(opt.dataroot, fullname)
     lmfile5 = os.path.join(opt.lm_dir, name+'.txt')
     lmfile68 = os.path.join(opt.lm_dir, name + '_68.txt')
+
     # 预处理数据
-    get_68lm(imgfile, lmfile5, lmfile68, detector, predictor)
+    # get_68lm(imgfile, lmfile5, lmfile68, detector, predictor)
+    f = open(savepath68, 'w')
+    print(landmarks_str, file=f)
+    f.close()
+    landmarks = np.loadtxt(savepath68)
+
+    ff = open(lmfile5, 'w')
+    lm = (landmarks[36] + landmarks[39]) / 2
+    print(int(lm[0]), int(lm[1]), file=ff)
+    lm = (landmarks[45] + landmarks[42]) / 2
+    print(int(lm[0]), int(lm[1]), file=ff)
+    lm = landmarks[30]
+    print(lm[0], lm[1], file=ff)
+    lm = landmarks[48]
+    print(lm[0], lm[1], file=ff)
+    lm = landmarks[54]
+    print(lm[0], lm[1], file=ff)
+    ff.close()
 
     imgs = []
     for part in ['eyel', 'eyer', 'nose', 'mouth']:
@@ -178,7 +196,7 @@ def run(
 
     print(imgs)
 
-    return PIL.Image.open(imgs[0]),PIL.Image.open(imgs[1])
+    return PIL.Image.open(imgs[1])
 
 
 def main():
@@ -218,16 +236,12 @@ def main():
         func,
         [
             gr.inputs.Image(type='file', label='Input Image'),
-            gr.inputs.Image(type='file', label='Input Mask'),
+            gr.inputs.Textbox(lines=1, label="Landmarks"),
         ],
         [
             gr.outputs.Image(
                 type='pil',
                 label='Result'),
-            gr.outputs.Image(
-                type='pil',
-                label='Result'),
-
         ],
         # examples=examples,
         theme=args.theme,