Delete app.py

app.py

@@ -1,255 +0,0 @@
-import gradio as gr
-from PIL import Image
-from urllib.parse import urlparse
-import requests
-import time
-import os
-
-from utils.gradio_helpers import parse_outputs, process_outputs
-
-# Function to verify the image file type and resize it if necessary
-def preprocess_image(image_path):
-    # Check if the file exists
-    if not os.path.exists(image_path):
-        raise FileNotFoundError(f"No such file: '{image_path}'")
-
-    # Get the file extension and make sure it's a valid image format
-    valid_extensions = ['jpg', 'jpeg', 'png', 'webp']
-    file_extension = image_path.split('.')[-1].lower()
-
-    if file_extension not in valid_extensions:
-        raise ValueError("Invalid file type. Only JPG, PNG, and WEBP are allowed.")
-    
-    # Open the image
-    with Image.open(image_path) as img:
-        width, height = img.size
-
-        # Check if any dimension exceeds 1024 pixels
-        if width > 1024 or height > 1024:
-            # Calculate the new size while maintaining aspect ratio
-            if width > height:
-                new_width = 1024
-                new_height = int((new_width / width) * height)
-            else:
-                new_height = 1024
-                new_width = int((new_height / height) * width)
-            
-            # Resize the image
-            img_resized = img.resize((new_width, new_height), Image.LANCZOS)
-            print(f"Resized image to {new_width}x{new_height}.")
-
-            # Save the resized image as 'resized_image.jpg'
-            output_path = 'resized_image.jpg'
-            img_resized.save(output_path, 'JPEG')
-            print(f"Resized image saved as {output_path}")
-            return output_path
-        else:
-            print("Image size is within the limit, no resizing needed.")
-            return image_path
-
-
-def display_uploaded_image(image_in):
-    return image_in
-
-def reset_parameters():
-    return gr.update(value=0), gr.update(value=0), gr.update(value=0), gr.update(value=0), gr.update(value=0), gr.update(value=0), gr.update(value=0), gr.update(value=0), gr.update(value=0), gr.update(value=0), gr.update(value=0), gr.update(value=0)
-
-names = ['image', 'rotate_pitch', 'rotate_yaw', 'rotate_roll', 'blink', 'eyebrow', 'wink', 'pupil_x', 'pupil_y', 'aaa', 'eee', 'woo', 'smile', 'src_ratio', 'sample_ratio', 'crop_factor', 'output_format', 'output_quality']
-
-def predict(request: gr.Request, *args, progress=gr.Progress(track_tqdm=True)):
-    headers = {'Content-Type': 'application/json'}
-
-    payload = {"input": {}}
-    
-    
-    base_url = "http://0.0.0.0:7860"
-    for i, key in enumerate(names):
-        value = args[i]
-        if value and (os.path.exists(str(value))):
-            value = f"{base_url}/gradio_api/file=" + value
-        if value is not None and value != "":
-            payload["input"][key] = value
-
-    time.sleep(0.5) 
-    response = requests.post("http://0.0.0.0:5000/predictions", headers=headers, json=payload)
-    
-    
-    if response.status_code == 201:
-        time.sleep(0.5)
-        follow_up_url = response.json()["urls"]["get"]
-        response = requests.get(follow_up_url, headers=headers)
-        while response.json()["status"] != "succeeded":
-            if response.json()["status"] == "failed":
-                raise gr.Error("The submission failed!")
-            response = requests.get(follow_up_url, headers=headers)
-            
-    if response.status_code == 200:
-        
-        json_response = response.json()
-        #If the output component is JSON return the entire output response 
-        if(outputs[0].get_config()["name"] == "json"):
-            return json_response["output"]
-        predict_outputs = parse_outputs(json_response["output"])
-        processed_outputs = process_outputs(predict_outputs)
-        print(f"processed_outputs: {processed_outputs}")
-        return tuple(processed_outputs) if len(processed_outputs) > 1 else processed_outputs[0]
-    else:
-        time.sleep(1)
-        if(response.status_code == 409):
-            raise gr.Error(f"Sorry, the Cog image is still processing. Try again in a bit.")
-        raise gr.Error(f"The submission failed! Error: {response.status_code}")
-
-
-css = '''
-#col-container{max-width: 800px;margin: 0 auto;}
-'''
-with gr.Blocks(css=css) as demo:
-    with gr.Column(elem_id="col-container"):
-        gr.Markdown("# Expression Editor")
-        gr.Markdown("Demo for expression-editor cog image by fofr")
-        with gr.Row():
-            with gr.Column():
-                image = gr.Image(
-                    label="Input image",
-                    sources=["upload"],
-                    type="filepath",
-                    height=180
-                )
-                with gr.Tab("HEAD"):
-                    with gr.Column():
-                        rotate_pitch = gr.Slider(
-                            label="Rotate Up-Down",
-                            value=0,
-                            minimum=-20, maximum=20
-                        )
-                        rotate_yaw = gr.Slider(
-                            label="Rotate Left-Right turn", 
-                            value=0,
-                            minimum=-20, maximum=20
-                        )
-                        rotate_roll = gr.Slider(
-                            label="Rotate Left-Right tilt", value=0,
-                            minimum=-20, maximum=20
-                        )
-                with gr.Tab("EYES"):
-                    with gr.Column():
-                        eyebrow = gr.Slider(
-                            label="Eyebrow", value=0,
-                            minimum=-10, maximum=15
-                        )
-                        with gr.Row():
-                            blink = gr.Slider(
-                                label="Blink", value=0,
-                                minimum=-20, maximum=5
-                            )
-                            
-                            wink = gr.Slider(
-                                label="Wink", value=0,
-                                minimum=0, maximum=25
-                            )
-                        with gr.Row():
-                            pupil_x = gr.Slider(
-                                label="Pupil X", value=0,
-                                minimum=-15, maximum=15
-                            )
-                            pupil_y = gr.Slider(
-                                label="Pupil Y", value=0,
-                                minimum=-15, maximum=15
-                            )
-                with gr.Tab("MOUTH"):
-                    with gr.Column():
-                        with gr.Row():
-                            aaa = gr.Slider(
-                                label="Aaa", value=0,
-                                minimum=-30, maximum=120
-                            )
-                            eee = gr.Slider(
-                                label="Eee", value=0,
-                                minimum=-20, maximum=15
-                            )
-                            woo = gr.Slider(
-                                label="Woo", value=0,
-                                minimum=-20, maximum=15
-                            )
-                        smile = gr.Slider(
-                            label="Smile", value=0,
-                            minimum=-0.3, maximum=1.3
-                        )
-                with gr.Tab("More Settings"):
-                    with gr.Column():
-                        src_ratio = gr.Number(
-                            label="Src Ratio", info='''Source ratio''', value=1
-                        )
-                        sample_ratio = gr.Slider(
-                            label="Sample Ratio", info='''Sample ratio''', value=1,
-                            minimum=-0.2, maximum=1.2
-                        )
-                        crop_factor = gr.Slider(
-                            label="Crop Factor", info='''Crop factor''', value=1.7,
-                            minimum=1.5, maximum=2.5
-                        )
-                        output_format = gr.Dropdown(
-                            choices=['webp', 'jpg', 'png'], label="output_format", info='''Format of the output images''', value="webp"
-                        )
-                        output_quality = gr.Number(
-                            label="Output Quality", info='''Quality of the output images, from 0 to 100. 100 is best quality, 0 is lowest quality.''', value=95
-                        )
-                with gr.Row():
-                    reset_btn = gr.Button("Reset")
-                    submit_btn = gr.Button("Submit")
-            with gr.Column():
-                result_image = gr.Image(elem_id="top")
-                gr.HTML("""
-                <div style="display: flex; flex-direction: column;justify-content: center; align-items: center; text-align: center;">
-                    <p style="display: flex;gap: 6px;">
-                         <a href="https://huggingface.co/spaces/fffiloni/expression-editor?duplicate=true">
-                            <img src="https://huggingface.co/datasets/huggingface/badges/resolve/main/duplicate-this-space-lg.svg" alt="Duplicate this Space">
-                        </a>
-                    </p>
-                    <p>to skip the queue and enjoy faster inference on the GPU of your choice </p>
-                </div>
-                """)
-
-    inputs = [image, rotate_pitch, rotate_yaw, rotate_roll, blink, eyebrow, wink, pupil_x, pupil_y, aaa, eee, woo, smile, src_ratio, sample_ratio, crop_factor, output_format, output_quality]
-    outputs = [result_image]
-
-    image.upload(
-        fn = preprocess_image,
-        inputs = [image],
-        outputs = [image],
-        queue = False
-    )
-
-    reset_btn.click(
-        fn = reset_parameters,
-        inputs = None,
-        outputs = [rotate_pitch, rotate_yaw, rotate_roll, blink, eyebrow, wink, pupil_x, pupil_y, aaa, eee, woo, smile],
-        queue = False
-    ).then(
-        fn=predict,
-        inputs=inputs,
-        outputs=outputs,
-        show_api=False
-    )
-    
-    submit_btn.click(
-        fn=predict,
-        inputs=inputs,
-        outputs=outputs,
-        show_api=False
-    )
-
-    rotate_pitch.release(fn=predict, inputs=inputs, outputs=outputs, show_progress="minimal", show_api=False)
-    rotate_yaw.release(fn=predict, inputs=inputs, outputs=outputs, show_progress="minimal", show_api=False)
-    rotate_roll.release(fn=predict, inputs=inputs, outputs=outputs, show_progress="minimal", show_api=False)
-    blink.release(fn=predict, inputs=inputs, outputs=outputs, show_progress="minimal", show_api=False)
-    eyebrow.release(fn=predict, inputs=inputs, outputs=outputs, show_progress="minimal", show_api=False)
-    wink.release(fn=predict, inputs=inputs, outputs=outputs, show_progress="minimal", show_api=False)
-    pupil_x.release(fn=predict, inputs=inputs, outputs=outputs, show_progress="minimal", show_api=False)
-    pupil_y.release(fn=predict, inputs=inputs, outputs=outputs, show_progress="minimal", show_api=False)
-    aaa.release(fn=predict, inputs=inputs, outputs=outputs, show_progress="minimal", show_api=False)
-    eee.release(fn=predict, inputs=inputs, outputs=outputs, show_progress="minimal", show_api=False)
-    woo.release(fn=predict, inputs=inputs, outputs=outputs, show_progress="minimal", show_api=False)
-    smile.release(fn=predict, inputs=inputs, outputs=outputs, show_progress="minimal", show_api=False)
-
-demo.queue(api_open=False).launch(share=False, show_error=True, show_api=False)