Upload app.py

app.py

@@ -0,0 +1,254 @@
+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}/file=" + value
+        if value is not None and value != "":
+            payload["input"][key] = value
+
+    time.sleep(0.4) 
+    response = requests.post("http://0.0.0.0:5000/predictions", headers=headers, json=payload)
+    
+    
+    if response.status_code == 201:
+        time.sleep(0.4)
+        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)
+        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: 720px;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)