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imseldrith

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DeepFakeAI

like 123

Running

@Nevertree Can you please send more logs which include command in it.

/usr/local/lib/python3.10/dist-packages/gradio_client/documentation.py:103: UserWarning: Could not get documentation group for <class 'gradio.mix.Parallel'>: No known documentation group for module 'gradio.mix'
warnings.warn(f"Could not get documentation group for {cls}: {exc}")
/usr/local/lib/python3.10/dist-packages/gradio_client/documentation.py:103: UserWarning: Could not get documentation group for <class 'gradio.mix.Series'>: No known documentation group for module 'gradio.mix'
warnings.warn(f"Could not get documentation group for {cls}: {exc}")
Running on local URL:
Running on public URL:

This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run gradio deploy from Terminal to deploy to Spaces (https://huggingface.co/spaces)
Started... python run.py --execution-providers cpu -s /tmp/gradio/4a9d17773d6515f6d2e68509d532fe4d3c609551/image.png -t /tmp/gradio/b9227fdcf2748456b276c60a476cb14e245418ee/image.png -o ./output/695d80c7-063b-4f12-a9a0-19f4ef81ead4/image.png --frame-processors face_swapper --face-analyser-direction left-right --face-recognition reference

Traceback (most recent call last):
File "/usr/local/lib/python3.10/dist-packages/gradio/routes.py", line 488, in run_predict
output = await app.get_blocks().process_api(
File "/usr/local/lib/python3.10/dist-packages/gradio/blocks.py", line 1434, in process_api
data = self.postprocess_data(fn_index, result["prediction"], state)
File "/usr/local/lib/python3.10/dist-packages/gradio/blocks.py", line 1341, in postprocess_data
prediction_value = block.postprocess(prediction_value)
File "/usr/local/lib/python3.10/dist-packages/gradio/components/image.py", line 318, in postprocess
return client_utils.encode_url_or_file_to_base64(y)
File "/usr/local/lib/python3.10/dist-packages/gradio_client/utils.py", line 718, in encode_url_or_file_to_base64
return encode_file_to_base64(path)
File "/usr/local/lib/python3.10/dist-packages/gradio_client/utils.py", line 691, in encode_file_to_base64
with open(f, "rb") as file:
FileNotFoundError: [Errno 2] No such file or directory: './output/695d80c7-063b-4f12-a9a0-19f4ef81ead4/image.png'
Started... python run.py --execution-providers cpu -s /tmp/gradio/d6f9ccccaf94b6cd3af540d7a8e795e21e90b837/image.png -t /tmp/gradio/d50058f7b0941d4711a2dec2923466bd985f8e6e/image.png -o ./output/695d80c7-063b-4f12-a9a0-19f4ef81ead4/image.png --frame-processors face_swapper --face-analyser-direction left-right --face-recognition reference --face-analyser-gender male

Traceback (most recent call last):
File "/usr/local/lib/python3.10/dist-packages/gradio/routes.py", line 488, in run_predict
output = await app.get_blocks().process_api(
File "/usr/local/lib/python3.10/dist-packages/gradio/blocks.py", line 1434, in process_api
data = self.postprocess_data(fn_index, result["prediction"], state)
File "/usr/local/lib/python3.10/dist-packages/gradio/blocks.py", line 1341, in postprocess_data
prediction_value = block.postprocess(prediction_value)
File "/usr/local/lib/python3.10/dist-packages/gradio/components/image.py", line 318, in postprocess
return client_utils.encode_url_or_file_to_base64(y)
File "/usr/local/lib/python3.10/dist-packages/gradio_client/utils.py", line 718, in encode_url_or_file_to_base64
return encode_file_to_base64(path)
File "/usr/local/lib/python3.10/dist-packages/gradio_client/utils.py", line 691, in encode_file_to_base64
with open(f, "rb") as file:
FileNotFoundError: [Errno 2] No such file or directory: './output/695d80c7-063b-4f12-a9a0-19f4ef81ead4/image.png'

@Nevertree which gradio version are you using.
Recommended: gradio==3.40.1

@imseldrith im using gradio==3.40.1, its still not working, i dont know why

Can you share colab link

@imseldrith here lol https://colab.research.google.com/drive/1Pd2MlO7eWbkPTWdGv0G7B7ucMc2A6jHH?usp=sharing

@Nevertree Thank you. I finally fixed issue now you can try.
Also In colab run below code directly instead of "python run.py" so that you can utilise colab GPU and do things faster:
Code:
import gradio as gr
import subprocess as sp
import os
import uuid
import time
import shutil

os.makedirs("./output", exist_ok=True)

def run(*args):
source, target, unique_id, *rest_args = args
if not os.path.exists(source):
return "Source file does not exist"
if not os.path.exists(target):
return "Target file does not exist"
remove_old_directories("./output", num_minutes=60)
filename = os.path.basename(target)
os.makedirs(f"./output/{unique_id}",exist_ok=True)
output = f"./output/{unique_id}/{filename}"
frame_processor = rest_args[0]
selected_frame_processors = ' '.join(frame_processor)

face_analyser_direction = rest_args[1]
face_recognition = rest_args[2]
face_analyser_gender = rest_args[3]

cmd = (
    f"python run.py --execution-providers cuda -s {source} -t {target} -o {output} "
    f"--frame-processors {selected_frame_processors} "
    f"--face-analyser-direction {face_analyser_direction} "
)
if face_recognition != 'none':
    cmd += f"--face-recognition {face_recognition} "
if face_analyser_gender != 'none':
    cmd += f"--face-analyser-gender {face_analyser_gender} "

if len(rest_args) > 4:
    skip_audio = rest_args[4]
    keep_fps = rest_args[5]
    keep_temp = rest_args[6]
    if skip_audio:
        cmd += "--skip-audio "
    if keep_fps:
        cmd += "--keep-fps "
    if keep_temp:
        cmd += "--keep-temp "

try:
    print("Started...", cmd)
    output_text = sp.run(cmd, shell=True, capture_output=True, text=True).stdout
    print(output_text)
    return output
except Exception as e:
    return f"An error occurred: {str(e)}"

def clear_output(unique_id):
try:
output_path = f"./output/{unique_id}"
if os.path.exists(output_path):
print("Trying to delete ")
for filename in os.listdir(output_path):
file_path = os.path.join(output_path, filename)
if os.path.isfile(file_path):
os.remove(file_path)
print(f"Output files in {output_path} are deleted")
return "Output files for unique_id deleted"
else:
print(f"Output files in {output_path} does not exist")
return "Output directory for (output_path} does not exist"
except Exception as e:
return f"An error occurred: {str(e)}"

def remove_old_directories(directory, num_minutes=60):
now = time.time()

for r, d, f in os.walk(directory):
    for dir_name in d:
        dir_path = os.path.join(r, dir_name)
        timestamp = os.path.getmtime(dir_path)
        age_minutes = (now - timestamp) / 60 # Convert to minutes

        if age_minutes >= num_minutes:
            try:
                print("Removing", dir_path)
                shutil.rmtree(dir_path)
                print("Directory removed:", dir_path)
            except Exception as e:
                print(e)
                pass

def get_theme() -> gr.Theme:
return gr.themes.Soft(
primary_hue = gr.themes.colors.red,
secondary_hue = gr.themes.colors.gray,
font = gr.themes.GoogleFont('Inter')
).set(
background_fill_primary = '*neutral_50',
block_label_text_size = '*text_sm',
block_title_text_size = '*text_sm'
)

with gr.Blocks(theme=get_theme(), title="DeepFakeAI 1.0.0") as ui:
with gr.Box():
gr.HTML('

with gr.Box():
    with gr.Column(scale=3):
       frame_processor_checkbox = gr.CheckboxGroup(
        choices = ['face_swapper', 'face_enhancer', 'frame_enhancer'],
        label = 'FRAME PROCESSORS',
        value = ['face_swapper']  # Default value
    )


with gr.Box():
    with gr.Column(scale=3):
        face_analyser_direction_dropdown = gr.Dropdown(
            label = 'FACE ANALYSER DIRECTION',
            choices = ['left-right', 'right-left', 'top-bottom', 'bottom-top', 'small-large', 'large-small'],
            value = 'left-right'
        )
        face_analyser_age_dropdown = gr.Dropdown(
            label = 'FACE RECOGNITION',
            choices = ['none'] + ['reference', 'many'],
            value = 'reference'
        )
        face_analyser_gender_dropdown = gr.Dropdown(
            label = 'FACE ANALYSER GENDER',
            choices = ['none'] + ['male', 'female'],
            value = 'none'
        )
        unique_id = gr.Textbox(value=str(uuid.uuid4()), visible=False)
with gr.Tab("Image:               "):
    source_image = gr.Image(type="filepath", label="SOURCE IMAGE")
    target_image = gr.Image(type="filepath", label="TARGET IMAGE")
    image_button = gr.Button("START")
    clear_button = gr.ClearButton(value="CLEAR")
    image_output = gr.Image(label="OUTPUT")
    clear_button.add(image_output)

    image_button.click(
        run,
        inputs=[source_image, target_image, unique_id, frame_processor_checkbox, face_analyser_direction_dropdown, face_analyser_age_dropdown, face_analyser_gender_dropdown],
        outputs=image_output
    )
    clear_button.click(fn=clear_output, inputs=unique_id)

with gr.Tab("Video:               "):
    source_image_video = gr.Image(type="filepath", label="SOURCE IMAGE")
    target_video = gr.Video(label="TARGET VIDEO")
    with gr.Box():
        skip_audio = gr.Checkbox(label="SKIP AUDIO")
        keep_fps = gr.Checkbox(label="KEEP FPS")
        keep_temp = gr.Checkbox(label="KEEP TEMP")
    video_button = gr.Button("START")
    clear_video_button = gr.ClearButton(value="CLEAR")
    video_output = gr.Video(label="OUTPUT")
    clear_video_button.add(video_output)
    video_button.click(
        run,
        inputs=[source_image_video, target_video, unique_id, frame_processor_checkbox, face_analyser_direction_dropdown, face_analyser_age_dropdown, face_analyser_gender_dropdown, skip_audio, keep_fps, keep_temp],
        outputs=video_output
    )
    clear_video_button.click(fn=clear_output, inputs=unique_id)

ui.launch(debug=True, share=True)