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victorisgeek
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9470555
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Parent(s):
b7ee6d8
Upload app.py
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app.py
CHANGED
@@ -26,7 +26,7 @@ from utils import trim_video, StreamerThread, ProcessBar, open_directory, split_
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## ------------------------------ USER ARGS ------------------------------
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-
parser = argparse.ArgumentParser(description="
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parser.add_argument("--out_dir", help="Default Output directory", default=os.getcwd())
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parser.add_argument("--batch_size", help="Gpu batch size", default=32)
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parser.add_argument("--cuda", action="store_true", help="Enable cuda", default=False)
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@@ -189,21 +189,21 @@ def process(
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yield "### \n
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load_face_analyser_model()
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-
yield "### \n
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load_face_swapper_model()
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if face_enhancer_name != "NONE":
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if face_enhancer_name not in cv2_interpolations:
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yield f"### \n
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FACE_ENHANCER = load_face_enhancer_model(name=face_enhancer_name, device=device)
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else:
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FACE_ENHANCER = None
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if enable_face_parser:
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yield "### \n
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load_face_parser_model()
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includes = mask_regions_to_list(mask_includes)
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@@ -221,7 +221,7 @@ def process(
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## ------------------------------ CONTENT CHECK ------------------------------
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yield "### \n
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if condition != "Specific Face":
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source_data = source_path, age
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else:
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@@ -237,7 +237,7 @@ def process(
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## ------------------------------ SWAP FUNC ------------------------------
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yield "### \n
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preds = []
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matrs = []
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count = 0
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@@ -251,13 +251,13 @@ def process(
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if USE_CUDA:
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image_grid = create_image_grid(batch_pred, size=128)
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PREVIEW = image_grid[:, :, ::-1]
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yield f"### \n
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## ------------------------------ FACE ENHANCEMENT ------------------------------
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generated_len = len(preds)
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if face_enhancer_name != "NONE":
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yield f"### \n
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for idx, pred in tqdm(enumerate(preds), total=generated_len, desc=f"Upscaling with {face_enhancer_name}"):
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enhancer_model, enhancer_model_runner = FACE_ENHANCER
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pred = enhancer_model_runner(pred, enhancer_model)
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@@ -267,7 +267,7 @@ def process(
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## ------------------------------ FACE PARSING ------------------------------
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if enable_face_parser:
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yield "### \n
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masks = []
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count = 0
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for batch_mask in get_parsed_mask(FACE_PARSER, preds, classes=includes, device=device, batch_size=BATCH_SIZE, softness=int(mask_soft_iterations)):
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@@ -278,7 +278,7 @@ def process(
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if len(batch_mask) > 1:
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image_grid = create_image_grid(batch_mask, size=128)
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PREVIEW = image_grid[:, :, ::-1]
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yield f"### \n
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masks = np.concatenate(masks, axis=0) if len(masks) >= 1 else masks
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else:
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masks = [None] * generated_len
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@@ -294,7 +294,7 @@ def process(
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## ------------------------------ PASTE-BACK ------------------------------
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yield "### \n
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def post_process(frame_idx, frame_img, split_preds, split_matrs, split_masks, enable_laplacian_blend, crop_mask, blur_amount, erode_amount):
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whole_img_path = frame_img
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whole_img = cv2.imread(whole_img_path)
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@@ -526,14 +526,14 @@ def slider_changed(show_frame, video_path, frame_index):
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def trim_and_reload(video_path, output_path, output_name, start_frame, stop_frame):
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yield video_path, f"### \n
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try:
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output_path = os.path.join(output_path, output_name)
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trimmed_video = trim_video(video_path, output_path, start_frame, stop_frame)
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yield trimmed_video, "### \n βοΈ Video trimmed and reloaded."
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except Exception as e:
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print(e)
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yield video_path, "### \n
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## ------------------------------ GRADIO GUI ------------------------------
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@@ -543,12 +543,11 @@ footer{display:none !important}
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"""
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with gr.Blocks(css=css) as interface:
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gr.Markdown("#
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gr.Markdown("### Face swap app based on insightface inswapper.")
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with gr.Row():
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with gr.Row():
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with gr.Column(scale=0.4):
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with gr.Tab("
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swap_option = gr.Dropdown(
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swap_options_list,
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info="Choose which face or faces in the target image to swap.",
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@@ -561,7 +560,7 @@ with gr.Blocks(css=css) as interface:
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value=25, label="Value", interactive=True, visible=False
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)
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with gr.Tab("
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detect_condition_dropdown = gr.Dropdown(
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detect_conditions,
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label="Condition",
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@@ -579,7 +578,7 @@ with gr.Blocks(css=css) as interface:
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)
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apply_detection_settings = gr.Button("Apply settings")
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with gr.Tab("
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output_directory = gr.Text(
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label="Output Directory",
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value=DEF_OUTPUT_PATH,
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@@ -592,7 +591,7 @@ with gr.Blocks(css=css) as interface:
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label="Keep output sequence", value=False, interactive=True
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)
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with gr.Tab("
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face_scale = gr.Slider(
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label="Face Scale",
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minimum=0,
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@@ -671,7 +670,7 @@ with gr.Blocks(css=css) as interface:
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label="Source face", type="filepath", interactive=True
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)
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with gr.
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for i in range(NUM_OF_SRC_SPECIFIC):
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idx = i + 1
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code = "\n"
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@@ -697,17 +696,17 @@ with gr.Blocks(css=css) as interface:
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value="Image",
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)
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with gr.
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image_input = gr.Image(
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label="Target Image", interactive=True, type="filepath"
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)
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with gr.
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vid_widget = gr.Video if USE_COLAB else gr.Text
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video_input = gr.Video(
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label="Target Video", interactive=True
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)
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with gr.Accordion("
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with gr.Column():
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with gr.Row():
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set_slider_range_btn = gr.Button(
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@@ -747,15 +746,15 @@ with gr.Blocks(css=css) as interface:
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"Trim and Reload", interactive=True
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)
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with gr.
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direc_input = gr.Text(label="Path", interactive=True)
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with gr.Column(scale=0.6):
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info = gr.Markdown(value="...")
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with gr.Row():
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swap_button = gr.Button("
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cancel_button = gr.Button("
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preview_image = gr.Image(label="Output", interactive=False)
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preview_video = gr.Video(
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@@ -764,14 +763,18 @@ with gr.Blocks(css=css) as interface:
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with gr.Row():
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output_directory_button = gr.Button(
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"
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)
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output_video_button = gr.Button(
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"
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)
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-
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-
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## ------------------------------ GRADIO EVENTS ------------------------------
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@@ -863,7 +866,8 @@ with gr.Blocks(css=css) as interface:
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swap_event = swap_button.click(
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fn=process, inputs=swap_inputs, outputs=swap_outputs, show_progress=True
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)
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-
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cancel_button.click(
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fn=stop_running,
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inputs=None,
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@@ -876,6 +880,7 @@ with gr.Blocks(css=css) as interface:
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end_frame_event,
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],
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show_progress=True,
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)
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output_directory_button.click(
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lambda: open_directory(path=WORKSPACE), inputs=None, outputs=None
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@@ -888,4 +893,5 @@ if __name__ == "__main__":
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if USE_COLAB:
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print("Running in colab mode")
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-
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## ------------------------------ USER ARGS ------------------------------
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parser = argparse.ArgumentParser(description="Free Face Swapper")
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parser.add_argument("--out_dir", help="Default Output directory", default=os.getcwd())
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parser.add_argument("--batch_size", help="Gpu batch size", default=32)
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parser.add_argument("--cuda", action="store_true", help="Enable cuda", default=False)
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yield "### \n π Loading face analyser model...", *ui_before()
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load_face_analyser_model()
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yield "### \n βοΈ Loading face swapper model...", *ui_before()
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load_face_swapper_model()
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if face_enhancer_name != "NONE":
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if face_enhancer_name not in cv2_interpolations:
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yield f"### \n π‘ Loading {face_enhancer_name} model...", *ui_before()
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FACE_ENHANCER = load_face_enhancer_model(name=face_enhancer_name, device=device)
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else:
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FACE_ENHANCER = None
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if enable_face_parser:
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yield "### \n π Loading face parsing model...", *ui_before()
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load_face_parser_model()
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includes = mask_regions_to_list(mask_includes)
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## ------------------------------ CONTENT CHECK ------------------------------
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yield "### \n π§Ώ Analysing face data...", *ui_before()
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if condition != "Specific Face":
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source_data = source_path, age
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else:
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## ------------------------------ SWAP FUNC ------------------------------
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yield "### \n π§Ά Generating faces...", *ui_before()
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preds = []
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matrs = []
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count = 0
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if USE_CUDA:
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image_grid = create_image_grid(batch_pred, size=128)
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PREVIEW = image_grid[:, :, ::-1]
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yield f"### \n 𧩠Generating face Batch {count}", *ui_before()
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## ------------------------------ FACE ENHANCEMENT ------------------------------
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generated_len = len(preds)
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if face_enhancer_name != "NONE":
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yield f"### \n π² Upscaling faces with {face_enhancer_name}...", *ui_before()
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for idx, pred in tqdm(enumerate(preds), total=generated_len, desc=f"Upscaling with {face_enhancer_name}"):
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enhancer_model, enhancer_model_runner = FACE_ENHANCER
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pred = enhancer_model_runner(pred, enhancer_model)
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## ------------------------------ FACE PARSING ------------------------------
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if enable_face_parser:
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yield "### \n π¨ Face-parsing mask...", *ui_before()
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masks = []
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count = 0
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for batch_mask in get_parsed_mask(FACE_PARSER, preds, classes=includes, device=device, batch_size=BATCH_SIZE, softness=int(mask_soft_iterations)):
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if len(batch_mask) > 1:
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image_grid = create_image_grid(batch_mask, size=128)
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PREVIEW = image_grid[:, :, ::-1]
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+
yield f"### \n πͺ Face parsing Batch {count}", *ui_before()
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masks = np.concatenate(masks, axis=0) if len(masks) >= 1 else masks
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else:
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masks = [None] * generated_len
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## ------------------------------ PASTE-BACK ------------------------------
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+
yield "### \n π§Ώ Pasting back...", *ui_before()
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def post_process(frame_idx, frame_img, split_preds, split_matrs, split_masks, enable_laplacian_blend, crop_mask, blur_amount, erode_amount):
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whole_img_path = frame_img
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whole_img = cv2.imread(whole_img_path)
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def trim_and_reload(video_path, output_path, output_name, start_frame, stop_frame):
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yield video_path, f"### \n π Trimming video frame {start_frame} to {stop_frame}..."
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try:
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output_path = os.path.join(output_path, output_name)
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trimmed_video = trim_video(video_path, output_path, start_frame, stop_frame)
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yield trimmed_video, "### \n βοΈ Video trimmed and reloaded."
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except Exception as e:
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print(e)
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yield video_path, "### \n π₯ Video trimming failed. See console for more info."
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## ------------------------------ GRADIO GUI ------------------------------
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"""
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with gr.Blocks(css=css) as interface:
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gr.Markdown("# π¦ FaceSwap with Enhnacer π¦")
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with gr.Row():
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with gr.Row():
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with gr.Column(scale=0.4):
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+
with gr.Tab("π Swap Condition"):
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swap_option = gr.Dropdown(
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swap_options_list,
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info="Choose which face or faces in the target image to swap.",
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value=25, label="Value", interactive=True, visible=False
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)
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563 |
+
with gr.Tab("β€οΈβπ©Ή Detection Settings"):
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detect_condition_dropdown = gr.Dropdown(
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detect_conditions,
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label="Condition",
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)
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apply_detection_settings = gr.Button("Apply settings")
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with gr.Tab("π Output Settings"):
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output_directory = gr.Text(
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label="Output Directory",
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value=DEF_OUTPUT_PATH,
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label="Keep output sequence", value=False, interactive=True
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)
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+
with gr.Tab("π€ Other Settings"):
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face_scale = gr.Slider(
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label="Face Scale",
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minimum=0,
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label="Source face", type="filepath", interactive=True
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)
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+
with gr.Group(visible=False) as specific_face:
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for i in range(NUM_OF_SRC_SPECIFIC):
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idx = i + 1
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code = "\n"
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value="Image",
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)
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698 |
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699 |
+
with gr.Group(visible=True) as input_image_group:
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700 |
image_input = gr.Image(
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701 |
label="Target Image", interactive=True, type="filepath"
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702 |
)
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703 |
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704 |
+
with gr.Group(visible=False) as input_video_group:
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705 |
vid_widget = gr.Video if USE_COLAB else gr.Text
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706 |
video_input = gr.Video(
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707 |
label="Target Video", interactive=True
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)
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709 |
+
with gr.Accordion("π Trim video", open=False):
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710 |
with gr.Column():
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711 |
with gr.Row():
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set_slider_range_btn = gr.Button(
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746 |
"Trim and Reload", interactive=True
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747 |
)
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748 |
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749 |
+
with gr.Group(visible=False) as input_directory_group:
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750 |
direc_input = gr.Text(label="Path", interactive=True)
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751 |
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752 |
with gr.Column(scale=0.6):
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753 |
info = gr.Markdown(value="...")
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754 |
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755 |
with gr.Row():
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756 |
+
swap_button = gr.Button("π Swap", variant="primary")
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757 |
+
cancel_button = gr.Button("π Cancel")
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758 |
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759 |
preview_image = gr.Image(label="Output", interactive=False)
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760 |
preview_video = gr.Video(
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763 |
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764 |
with gr.Row():
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765 |
output_directory_button = gr.Button(
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766 |
+
"π", interactive=False, visible=False
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767 |
)
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768 |
output_video_button = gr.Button(
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769 |
+
"π", interactive=False, visible=False
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770 |
)
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771 |
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772 |
+
with gr.Group():
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773 |
+
with gr.Row():
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774 |
+
gr.Markdown(
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775 |
+
"### [π€ Welcome to my GitHub π€](https://github.com/victorgeel)"
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776 |
+
)
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777 |
+
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778 |
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779 |
## ------------------------------ GRADIO EVENTS ------------------------------
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780 |
|
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866 |
swap_event = swap_button.click(
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867 |
fn=process, inputs=swap_inputs, outputs=swap_outputs, show_progress=True
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868 |
)
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869 |
+
|
870 |
+
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871 |
cancel_button.click(
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872 |
fn=stop_running,
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873 |
inputs=None,
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|
880 |
end_frame_event,
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881 |
],
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882 |
show_progress=True,
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883 |
+
|
884 |
)
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885 |
output_directory_button.click(
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886 |
lambda: open_directory(path=WORKSPACE), inputs=None, outputs=None
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|
893 |
if USE_COLAB:
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894 |
print("Running in colab mode")
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895 |
|
896 |
+
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897 |
+
interface.launch(share=USE_COLAB, max_threads=10)
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