test

app.py

@@ -1,48 +1,28 @@
-import os
 import gradio as gr
-from gradio_imageslider import ImageSlider
-from loadimg import load_img
-
 import requests
 import base64
+import os
 from PIL import Image
 from io import BytesIO
 import numpy as np
+from gradio_imageslider import ImageSlider  # Assicurati di avere questa libreria installata
+from loadimg import load_img  # Assicurati che questa funzione sia disponibile
 
-output_folder = 'output_images'
-if not os.path.exists(output_folder):
-    os.makedirs(output_folder)
-
+from dotenv import load_dotenv
 
-def fn(image):
-    im = load_img(image, output_type="pil")
-    im = im.convert("RGB")
-    origin = im.copy()
-    image = process(im)
-    image_path = os.path.join(output_folder, "no_bg_image.png")
-    image.save(image_path)
-    return (image, origin), image_path
+# Carica le variabili di ambiente dal file .env
+load_dotenv()
 
+def numpy_to_pil(image):
+    """Convert a numpy array to a PIL Image."""
+    if image.dtype == np.uint8:  # Most common case
+        mode = "RGB"
+    else:
+        mode = "F"  # Floating point
+    return Image.fromarray(image.astype('uint8'), mode)
 
-def process(image):
-    def numpy_to_pil(image):
-        """Convert a numpy array to a PIL Image."""
-        if not isinstance(image, np.ndarray):
-            print(f"Type of input: {type(image)}")
-            raise TypeError("Input must be a numpy array")
-
-            # Determine the mode based on the shape and dtype of the image
-        if image.ndim == 2:  # Grayscale image
-            mode = "L"
-        elif image.ndim == 3 and image.shape[2] == 3:  # RGB image
-            mode = "RGB"
-        elif image.ndim == 3 and image.shape[2] == 4:  # RGBA image
-            mode = "RGBA"
-        else:
-            raise ValueError("Unsupported image shape: {}".format(image.shape))
-
-        return Image.fromarray(image, mode)
 
+def process_image(image):
     image = numpy_to_pil(image)  # Convert numpy array to PIL Image
     buffered = BytesIO()
     image.save(buffered, format="PNG")
@@ -54,40 +34,21 @@ def process(image):
     result = response.json()
     processed_image_b64 = result["processed_image"]
     processed_image = Image.open(BytesIO(base64.b64decode(processed_image_b64)))
-    return processed_image  # Return the original and processed images
-
+    return [image, processed_image]  # Return the original and processed images
 
-def process_file(f):
-    name_path = f.rsplit(".", 1)[0] + ".png"
-    im = load_img(f, output_type="pil")
-    im = im.convert("RGB")
-    transparent = process(im)
-    transparent.save(name_path)
-    return name_path
-
-
-slider1 = ImageSlider(label="RMBG-2.0", type="pil")
-slider2 = ImageSlider(label="RMBG-2.0", type="pil")
-image = gr.Image(label="Upload an image")
-image2 = gr.Image(label="Upload an image", type="filepath")
-text = gr.Textbox(label="Paste an image URL")
-png_file = gr.File(label="output png file")
 
+# Carica l'esempio di immagine
 chameleon = load_img("elephant.jpg", output_type="pil")
 
-url = "http://farm9.staticflickr.com/8488/8228323072_76eeddfea3_z.jpg"
-
-tab1 = gr.Interface(
-    fn, inputs=image, outputs=[slider1, gr.File(label="output png file")], examples=[chameleon], api_name="image"
-)
-
-tab2 = gr.Interface(fn, inputs=text, outputs=[slider2, gr.File(label="output png file")], examples=[url],
-                    api_name="text")
-tab3 = gr.Interface(process_file, inputs=image2, outputs=png_file, examples=["elephant.jpg"], api_name="png")
-
-demo = gr.TabbedInterface(
-    [tab1, tab2], ["input image", "input url"], title=" background removal"
+image = gr.Image(label="Upload a photo")
+output_slider = ImageSlider(label="Processed photo", type="pil")
+demo = gr.Interface(
+    fn=process_image,
+    inputs=image,
+    outputs=output_slider,
+    title="Magic Eraser",
+    examples=[["elephant.jpg"]]  # Esempio locale
 )
 
 if __name__ == "__main__":
-    demo.launch(show_error=True)
+    demo.launch()