New

open.py

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+import gradio as gr
+from PIL import Image
+import numpy as np
+import cv2
+
+# Fonction pour charger et afficher l'image
+def load_image(image):
+    return image
+
+# Fonction pour appliquer un négatif
+def apply_negative(image):
+    img_np = np.array(image)
+    negative = 255 - img_np
+    return Image.fromarray(negative)
+
+# Fonction pour binariser une image
+def binarize_image(image, threshold):
+    img_np = np.array(image.convert('L'))  # Convertir en niveaux de gris
+    _, binary = cv2.threshold(img_np, threshold, 255, cv2.THRESH_BINARY)
+    return Image.fromarray(binary)
+
+# Interface Gradio
+def image_processing(image, operation, threshold=128):
+    if operation == "Négatif":
+        return apply_negative(image)
+    elif operation == "Binarisation":
+        return binarize_image(image, threshold)
+    return image
+
+# Interface Gradio
+with gr.Blocks() as demo:
+    gr.Markdown("## Projet de Traitement d'Image")
+    
+    with gr.Row():
+        image_input = gr.Image(type="pil", label="Charger Image")
+        operation = gr.Radio(["Négatif", "Binarisation"], label="Opération à effectuer", value="Négatif")
+        threshold = gr.Slider(0, 255, 128, label="Seuil de binarisation", visible=False)
+    
+    image_output = gr.Image(label="Image Modifiée")
+
+    def update_threshold(operation):
+        if operation == "Binarisation":
+            return gr.update(visible=True)
+        return gr.update(visible=False)
+    
+    operation.change(update_threshold, inputs=operation, outputs=threshold)
+    
+    submit_button = gr.Button("Appliquer")
+    submit_button.click(image_processing, inputs=[image_input, operation, threshold], outputs=image_output)
+
+# Lancer l'application Gradio
+demo.launch()

requirements.txt

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+gradio==3.41.2
+Pillow==10.0.0
+opencv-python==4.10.0.84
+numpy==1.26.0