add aphla image
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d5db3a3020
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@ -56,17 +56,18 @@ def detect(net, img, device):
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return bboxlist
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def batch_detect(net, imgs, device):
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imgs = imgs - np.array([104, 117, 123])
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imgs = imgs.transpose(0, 3, 1, 2)
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def batch_detect(net, images, device):
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rgb = images[:, :, :, :3]
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rgb = rgb - np.array([104, 117, 123])
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rgb = rgb.transpose(0, 3, 1, 2)
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if 'cuda' in device:
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torch.backends.cudnn.benchmark = True
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imgs = torch.from_numpy(imgs).float().to(device)
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BB, CC, HH, WW = imgs.size()
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images1 = torch.from_numpy(rgb).float().to(device)
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BB, CC, HH, WW = images1.size()
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with torch.no_grad():
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olist = net(imgs)
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olist = net(images1)
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bboxlist = []
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for i in range(len(olist) // 2):
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@ -44,7 +44,6 @@ class HumanContext:
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logging.info(f'face images length: {face_images_length}')
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print(f'face images length: {face_images_length}')
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def __del__(self):
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print(f'HumanContext: __del__')
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object_stop(self._asr)
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@ -30,8 +30,9 @@ class VideoRender(BaseRender):
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clock_time = self._play_clock.clock_time()
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time_difference = clock_time - ps
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print("Video frame time", clock_time, ps, time_difference)
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if abs(time_difference) > self._play_clock.audio_diff_threshold:
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if self._diff_avg_count < 3:
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if self._diff_avg_count < 5:
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self._diff_avg_count += 1
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else:
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if time_difference < -self._play_clock.audio_diff_threshold:
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@ -62,7 +63,7 @@ class VideoRender(BaseRender):
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except:
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print('resize error')
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return
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combine_frame[y1:y2, x1:x2] = res_frame
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combine_frame[y1:y2, x1:x2, :3] = res_frame
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image = combine_frame
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# image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
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10
ui.py
10
ui.py
@ -57,7 +57,7 @@ class App(customtkinter.CTk):
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# self.main_button_1.grid(row=2, column=2, padx=(20, 20), pady=(20, 20), sticky="nsew")
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background = os.path.join(current_file_path, 'data', 'background', 'background.webp')
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logger.info(f'background: {background}')
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# self._background = ImageTk.PhotoImage(read_image(background))
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self._background = read_image(background).convert("RGBA")
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self._init_image_canvas()
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@ -105,7 +105,13 @@ class App(customtkinter.CTk):
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image = cv2.resize(image, (int(iwidth * height / iheight), int(height)), interpolation=cv2.INTER_AREA)
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img = Image.fromarray(image)
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imgtk = ImageTk.PhotoImage(image=img)
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bg_width, bg_height = self._background.size
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fg_width, fg_height = img.size
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x = (bg_width - fg_width) // 2
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y = (bg_height - fg_height) // 2
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self._background.paste(img, (x, y), img)
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imgtk = ImageTk.PhotoImage(self._background)
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self._canvas.delete("all")
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@ -36,7 +36,7 @@ def read_images(img_list):
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print(f'read image path:{img_path}')
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# frame = cv2.imread(img_path, cv2.IMREAD_UNCHANGED)
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frame = Image.open(img_path)
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frame = frame.convert("RGBA")
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# frame = frame.convert("RGBA")
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frame = np.array(frame)
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frames.append(frame)
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return frames
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@ -179,7 +179,7 @@ def load_avatar(path, img_size, device):
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face_frames = []
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coord_frames = []
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for face, coord in face_det_results:
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resized_crop_frame = cv2.resize(face, (img_size, img_size))
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resized_crop_frame = cv2.resize(face[:, :, :3], (img_size, img_size))
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face_frames.append(resized_crop_frame)
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coord_frames.append(coord)
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