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Upload app.py
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app.py
CHANGED
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@@ -2,6 +2,7 @@ import os
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import cv2
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import glob
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import time
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import shutil
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import argparse
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import platform
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@@ -188,21 +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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@@ -220,7 +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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@@ -236,7 +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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@@ -250,13 +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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@@ -266,7 +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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@@ -277,7 +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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@@ -293,7 +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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@@ -349,7 +350,7 @@ def process(
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temp_path = os.path.join(output_path, output_name, "sequence")
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os.makedirs(temp_path, exist_ok=True)
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yield "### \n
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image_sequence = []
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cap = cv2.VideoCapture(video_path)
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curr_idx = 0
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@@ -366,12 +367,12 @@ def process(
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for info_update in swap_process(image_sequence):
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yield info_update
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yield "### \n
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output_video_path = os.path.join(output_path, output_name + ".mp4")
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merge_img_sequence_from_ref(video_path, image_sequence, output_video_path)
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if os.path.exists(temp_path) and not keep_output_sequence:
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yield "### \n
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shutil.rmtree(temp_path)
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WORKSPACE = output_path
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@@ -489,7 +490,7 @@ def video_changed(video_path):
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def analyse_settings_changed(detect_condition, detection_size, detection_threshold):
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yield "### \n
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global FACE_ANALYSER
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global DETECT_CONDITION
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DETECT_CONDITION = detect_condition
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@@ -525,14 +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
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except Exception as e:
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print(e)
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yield video_path, "### \n โVideo trimming failed. See console for more info."
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## ------------------------------ GRADIO GUI ------------------------------
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@@ -541,13 +542,13 @@ css = """
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footer{display:none !important}
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"""
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with gr.Blocks(
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gr.Markdown("#
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gr.Markdown("###
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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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@@ -560,7 +561,7 @@ with gr.Blocks(theme='earneleh/paris') 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("๐Detection 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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@@ -578,7 +579,7 @@ with gr.Blocks(theme='earneleh/paris') 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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@@ -591,7 +592,7 @@ with gr.Blocks(theme='earneleh/paris') 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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@@ -670,7 +671,7 @@ with gr.Blocks(theme='earneleh/paris') 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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@@ -696,17 +697,17 @@ with gr.Blocks(theme='earneleh/paris') 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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@@ -746,15 +747,15 @@ with gr.Blocks(theme='earneleh/paris') 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.
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info = gr.Markdown(value="...")
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with gr.Row():
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swap_button = gr.Button("๐ฏ Swap", variant="primary")
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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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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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gr.Markdown(
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"### [๐ญ Sponsor]"
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)
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gr.Markdown(
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"### [๐ฅ๏ธ Source code](https://huggingface.co/spaces/victorisgeek/SwapFace2Pon)"
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)
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gr.Markdown(
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"### [ ๐งฉ Playground](https://huggingface.co/spaces/victorisgeek/SwapFace2Pon)"
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)
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gr.Markdown(
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"### [๐ธ Run in Colab](https://colab.research.google.com/github/victorgeel/FaceSwapNoNfsw/blob/main/SwapFace.ipynb)"
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)
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gr.Markdown(
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"### [๐ค Modified Version](https://github.com/victorgeel/FaceSwapNoNfsw)"
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)
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## ------------------------------ GRADIO EVENTS ------------------------------
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if USE_COLAB:
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print("Running in colab mode")
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interface.queue(concurrency_count=2, max_size=20).launch(share=
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import cv2
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import glob
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import time
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import torch
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import shutil
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import argparse
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import platform
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yield "### \n โ Loading face analyser model...", *ui_before()
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load_face_analyser_model()
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yield "### \n โ 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 โ 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 โ 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 โ 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 โ 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 โ 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 โ 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 โ 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 โ 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 โ 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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temp_path = os.path.join(output_path, output_name, "sequence")
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os.makedirs(temp_path, exist_ok=True)
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+
yield "### \n โ Extracting video frames...", *ui_before()
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image_sequence = []
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cap = cv2.VideoCapture(video_path)
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curr_idx = 0
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for info_update in swap_process(image_sequence):
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yield info_update
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+
yield "### \n โ Merging sequence...", *ui_before()
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output_video_path = os.path.join(output_path, output_name + ".mp4")
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merge_img_sequence_from_ref(video_path, image_sequence, output_video_path)
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| 374 |
if os.path.exists(temp_path) and not keep_output_sequence:
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+
yield "### \n โ Removing temporary files...", *ui_before()
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shutil.rmtree(temp_path)
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WORKSPACE = output_path
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def analyse_settings_changed(detect_condition, detection_size, detection_threshold):
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+
yield "### \n โ Applying new values..."
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global FACE_ANALYSER
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global DETECT_CONDITION
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DETECT_CONDITION = detect_condition
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| 527 |
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| 528 |
def trim_and_reload(video_path, output_path, output_name, start_frame, stop_frame):
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| 529 |
+
yield video_path, f"### \n โ 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 โ๏ธ Video trimmed and reloaded."
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| 534 |
except Exception as e:
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print(e)
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| 536 |
+
yield video_path, "### \n โ Video trimming failed. See console for more info."
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| 537 |
|
| 538 |
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| 539 |
## ------------------------------ GRADIO GUI ------------------------------
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| 542 |
footer{display:none !important}
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"""
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| 544 |
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| 545 |
+
with gr.Blocks(css=css) as interface:
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| 546 |
+
gr.Markdown("# ๐ญ Swapper")
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| 547 |
+
gr.Markdown("### Face swap app based on insightface inswapper.")
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| 548 |
with gr.Row():
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| 549 |
with gr.Row():
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| 550 |
with gr.Column(scale=0.4):
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| 551 |
+
with gr.Tab("๐ Swap Condition"):
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| 552 |
swap_option = gr.Dropdown(
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| 553 |
swap_options_list,
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| 554 |
info="Choose which face or faces in the target image to swap.",
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| 561 |
value=25, label="Value", interactive=True, visible=False
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| 562 |
)
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| 563 |
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| 564 |
+
with gr.Tab("๐ Detection Settings"):
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| 565 |
detect_condition_dropdown = gr.Dropdown(
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| 566 |
detect_conditions,
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label="Condition",
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| 579 |
)
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| 580 |
apply_detection_settings = gr.Button("Apply settings")
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| 582 |
+
with gr.Tab("๐ง Output Settings"):
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output_directory = gr.Text(
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label="Output Directory",
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| 585 |
value=DEF_OUTPUT_PATH,
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|
| 592 |
label="Keep output sequence", value=False, interactive=True
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| 593 |
)
|
| 594 |
|
| 595 |
+
with gr.Tab("๐จ Other Settings"):
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| 596 |
face_scale = gr.Slider(
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| 597 |
label="Face Scale",
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| 598 |
minimum=0,
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|
| 671 |
label="Source face", type="filepath", interactive=True
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| 672 |
)
|
| 673 |
|
| 674 |
+
with gr.Box(visible=False) as specific_face:
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| 675 |
for i in range(NUM_OF_SRC_SPECIFIC):
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| 676 |
idx = i + 1
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| 677 |
code = "\n"
|
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|
| 697 |
value="Image",
|
| 698 |
)
|
| 699 |
|
| 700 |
+
with gr.Box(visible=True) as input_image_group:
|
| 701 |
image_input = gr.Image(
|
| 702 |
label="Target Image", interactive=True, type="filepath"
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| 703 |
)
|
| 704 |
|
| 705 |
+
with gr.Box(visible=False) as input_video_group:
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| 706 |
vid_widget = gr.Video if USE_COLAB else gr.Text
|
| 707 |
video_input = gr.Video(
|
| 708 |
label="Target Video", interactive=True
|
| 709 |
)
|
| 710 |
+
with gr.Accordion("๐ช Trim video", open=False):
|
| 711 |
with gr.Column():
|
| 712 |
with gr.Row():
|
| 713 |
set_slider_range_btn = gr.Button(
|
|
|
|
| 747 |
"Trim and Reload", interactive=True
|
| 748 |
)
|
| 749 |
|
| 750 |
+
with gr.Box(visible=False) as input_directory_group:
|
| 751 |
direc_input = gr.Text(label="Path", interactive=True)
|
| 752 |
|
| 753 |
+
with gr.Column(scale=0.6):
|
| 754 |
info = gr.Markdown(value="...")
|
| 755 |
|
| 756 |
with gr.Row():
|
| 757 |
swap_button = gr.Button("๐ฏ Swap", variant="primary")
|
| 758 |
+
cancel_button = gr.Button("โ Cancel")
|
| 759 |
|
| 760 |
preview_image = gr.Image(label="Output", interactive=False)
|
| 761 |
preview_video = gr.Video(
|
|
|
|
| 764 |
|
| 765 |
with gr.Row():
|
| 766 |
output_directory_button = gr.Button(
|
| 767 |
+
"๐", interactive=False, visible=False
|
| 768 |
)
|
| 769 |
output_video_button = gr.Button(
|
| 770 |
+
"๐บ", interactive=False, visible=False
|
| 771 |
)
|
| 772 |
|
| 773 |
+
|
| 774 |
+
|
|
|
|
|
|
|
|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
| 775 |
|
| 776 |
## ------------------------------ GRADIO EVENTS ------------------------------
|
| 777 |
|
|
|
|
| 888 |
if USE_COLAB:
|
| 889 |
print("Running in colab mode")
|
| 890 |
|
| 891 |
+
interface.queue(concurrency_count=2, max_size=20).launch(share=False)
|