Update src/gradio_pipeline.py

src/gradio_pipeline.py

@@ -92,6 +92,35 @@ class GradioPipeline(LivePortraitPipeline):
             return out, out_to_ori_blend
 
 
+    def execute_image_lip(self, input_lip_ratio: float, input_image, flag_do_crop = True):
+        """ for single image retargeting
+        """
+        # disposable feature
+        f_s_user, x_s_user, source_lmk_user, crop_M_c2o, mask_ori, img_rgb = \
+        self.prepare_retargeting(input_image, flag_do_crop)
+
+        if input_lip_ratio is None:
+            raise gr.Error("Invalid ratio input 💥!", duration=5)
+        else:
+            x_s_user = x_s_user.to("cuda")
+            f_s_user = f_s_user.to("cuda")
+
+            combined_lip_ratio_tensor = self.live_portrait_wrapper.calc_combined_lip_ratio([[input_lip_ratio]], source_lmk_user)
+            lip_delta = self.live_portrait_wrapper.retarget_lip(x_s_user, combined_lip_ratio_tensor)
+            num_kp = x_s_user.shape[1]
+            
+            # default: use x_s
+            x_d_new = x_s_user + lip_delta.reshape(-1, num_kp, 3)
+            
+            # D(W(f_s; x_s, x′_d))
+            out = self.live_portrait_wrapper.warp_decode(f_s_user, x_s_user, x_d_new)
+            out = self.live_portrait_wrapper.parse_output(out['out'])[0]
+            out_to_ori_blend = paste_back(out, crop_M_c2o, img_rgb, mask_ori)
+            
+            # gr.Info("Run successfully!", duration=2)
+            return out_to_ori_blend
+
+
     def prepare_retargeting(self, input_image, flag_do_crop = True):
         """ for single image retargeting
         """
@@ -119,26 +148,4 @@ class GradioPipeline(LivePortraitPipeline):
             # when press the clear button, go here
             raise gr.Error("Please upload a source portrait as the retargeting input 🤗🤗🤗", duration=5)
 
-    def init_retargeting_image(self, retargeting_source_scale: float, source_eye_ratio: float, source_lip_ratio:float, input_image = None):
-        """ initialize the retargeting slider
-        """
-        if input_image != None:
-            args_user = {'scale': retargeting_source_scale}
-            self.args = update_args(self.args, args_user)
-            self.cropper.update_config(self.args.__dict__)
-            # inference_cfg = self.live_portrait_wrapper.inference_cfg
-            ######## process source portrait ########
-            img_rgb = load_img_online(input_image, mode='rgb', max_dim=1280, n=16)
-            log(f"Load source image from {input_image}.")
-            #crop_info = self.cropper.crop_source_image(img_rgb, self.cropper.crop_cfg)
-            crop_info = self.cropper.crop_single_image(img_rgb)
-            if crop_info is None:
-                raise gr.Error("Source portrait NO face detected", duration=2)
-            source_eye_ratio = calc_eye_close_ratio(crop_info['lmk_crop'][None])
-            source_lip_ratio = calc_lip_close_ratio(crop_info['lmk_crop'][None])
-            self.source_eye_ratio = round(float(source_eye_ratio.mean()), 2)
-            self.source_lip_ratio = round(float(source_lip_ratio[0][0]), 2)
-            log("Calculating eyes-open and lip-open ratios successfully!")
-            return self.source_eye_ratio, self.source_lip_ratio
-        else:
-            return source_eye_ratio, source_lip_ratio
+