Update app.py

app.py

@@ -8,6 +8,7 @@ from itertools import cycle
 import os
 from datetime import datetime
 import gradio as gr
+import tempfile
 
 # Load model and processor
 model_id = "fushh7/llmdet_swin_large_hf"
@@ -30,43 +31,32 @@ BOX_COLORS = [
     "orange", "chartreuse"
 ]
 
-
-def save_cropped_images(original_image, boxes, labels, scores, output_dir="static/output_crops"):
+def save_cropped_images(original_image, boxes, labels, scores):
     """
-    Salva ogni regione ritagliata definita dalle bounding box in file separati.
-
+    Salva ogni regione ritagliata definita dalle bounding box in file temporanei.
+    
     :param original_image: Immagine PIL originale
     :param boxes: Lista di bounding box [x_min, y_min, x_max, y_max]
     :param labels: Lista di etichette per ogni box
     :param scores: Lista di punteggi di confidenza
-    :param output_dir: Directory base dove salvare le immagini
-    :return: Lista dei percorsi dei file salvati
+    :return: Lista dei percorsi dei file temporanei salvati
     """
-    # Crea una directory con timestamp per evitare sovrascritture
-    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
-    output_path = os.path.join(output_dir, f"detections_{timestamp}")
-    os.makedirs(output_path, exist_ok=True)
-
     saved_paths = []
-
+    
     for i, (box, label, score) in enumerate(zip(boxes, labels, scores)):
-        # Pulisci il label per usarlo nel nome del file
-        clean_label = "".join(c if c.isalnum() else "_" for c in label)
-
+        # Crea un file temporaneo
+        with tempfile.NamedTemporaryFile(suffix=".jpg", delete=False) as tmp_file:
+            filepath = tmp_file.name
+        
         # Ritaglia la regione dall'immagine originale
         cropped_img = original_image.crop(box)
-
-        # Crea il nome del file
-        filename = f"crop_{i}_{clean_label}_{score:.2f}.jpg"
-        filepath = os.path.join(output_path, filename)
-
+        
         # Salva l'immagine ritagliata
         cropped_img.save(filepath)
         saved_paths.append(filepath)
-
+    
     return saved_paths
 
-
 def draw_boxes(image, boxes, labels, scores, colors=BOX_COLORS, font_path="arial.ttf", font_size=16):
     """
     Draw bounding boxes and labels on a PIL Image.
@@ -146,9 +136,9 @@ def detect_and_draw(
     box_threshold: float = 0.14,
     text_threshold: float = 0.13,
     save_crops: bool = True
-) -> Image.Image:
+):
     """
-    Detect objects described in `text_query`, draw boxes, return the image.
+    Detect objects described in `text_query`, draw boxes, return the image and crops.
     Note: `text_query` must be lowercase and each concept ends with a dot
           (e.g. 'a cat. a remote control.')
     """
@@ -180,42 +170,91 @@ def detect_and_draw(
         labels = results.get("text_labels", results.get("labels", [])),
         scores = results["scores"]
     )
+    
+    # Lista per i percorsi dei crop
+    crop_paths = []
+    
     if save_crops:
-        saved_paths = save_cropped_images(
+        crop_paths = save_cropped_images(
             img,
             boxes=results["boxes"].cpu().numpy(),
             labels=results.get("text_labels", results.get("labels", [])),
             scores=results["scores"]
         )
-        print(f"Saved {len(saved_paths)} cropped images to: {os.path.dirname(saved_paths[0])}")
+        print(f"Generated {len(crop_paths)} cropped images")
 
-    return img_out
+    return img_out, crop_paths
 
 # Create example list
 examples = [
     ["examples/stickers(1).jpg", "stickers. labels.", 0.24, 0.23],
-#    ["examples/IMG_8920.jpeg", "bin. water bottle. hand. shoe.", 0.4, 0.3],
-#    ["examples/IMG_9435.jpeg", "lettuce. orange slices (group). eggs (group). cheese (group). red cabbage. pear slices (group).", 0.4, 0.3],
 ]
 
+# Funzione per pulire i file temporanei dopo l'uso
+def cleanup_temp_files(crop_paths):
+    for path in crop_paths:
+        try:
+            os.unlink(path)
+        except:
+            pass
+
 # Create Gradio demo
-app = gr.Interface(
-    fn      = detect_and_draw,
-    inputs  = [
-        gr.Image(type="pil", label="Image"),
-        gr.Textbox(value="stickers. labels. postcards.",
-                   label="Text Query (lowercase, end each with '.', for example 'a bird. a tree.')"),
-        gr.Slider(0.0, 1.0, 0.14, 0.05, label="Box Threshold"),
-        gr.Slider(0.0, 1.0, 0.13, 0.05, label="Text Threshold")
-    ],
-    outputs = gr.Image(type="pil", label="Detections"),
-    title   = "Sticker Geo Tagger",
-    description = f"""Upload an image containings stickers and adjust thresholds to see detections.
-    <a href='/output_crops/' target='crops'>output_crops</a>
-    """,
-    examples = examples,
-    cache_examples = True,
-)
-
-#app.launch(server_name="0.0.0.0", server_port=22590, root_path="/stikkiers2", share=False)
-app.launch(server_name="0.0.0.0", share=False)
+with gr.Blocks() as demo:
+    gr.Markdown("# Sticker Geo Tagger")
+    gr.Markdown("Upload an image containing stickers and adjust thresholds to see detections.")
+    
+    with gr.Row():
+        with gr.Column():
+            image_input = gr.Image(type="pil", label="Input Image")
+            text_query = gr.Textbox(
+                value="stickers. labels. postcards.",
+                label="Text Query (lowercase, end each with '.', for example 'a bird. a tree.')"
+            )
+            box_threshold = gr.Slider(0.0, 1.0, 0.14, step=0.05, label="Box Threshold")
+            text_threshold = gr.Slider(0.0, 1.0, 0.13, step=0.05, label="Text Threshold")
+            submit_btn = gr.Button("Detect")
+        
+        with gr.Column():
+            image_output = gr.Image(type="pil", label="Detections")
+    
+    # Galleria per i crop
+    gallery = gr.Gallery(
+        label="Detected Crops",
+        columns=[4],
+        rows=[2],
+        object_fit="contain",
+        height="auto"
+    )
+    
+    # Esempi
+    gr.Examples(
+        examples=examples,
+        inputs=[image_input, text_query, box_threshold, text_threshold],
+        outputs=[image_output, gallery],
+        fn=detect_and_draw,
+        cache_examples=True
+    )
+    
+    # Pulsante di submit
+    submit_btn.click(
+        fn=detect_and_draw,
+        inputs=[image_input, text_query, box_threshold, text_threshold],
+        outputs=[image_output, gallery]
+    )
+    
+    # Pulisci i file temporanei quando viene caricato un nuovo esempio
+    demo.load(
+        fn=lambda: None,
+        inputs=None,
+        outputs=None,
+        _js="""
+        function() {
+            // Pulisci i file temporanei quando la pagina viene ricaricata
+            fetch('/cleanup_temp_files', {method: 'POST'});
+            return [];
+        }
+        """
+    )
+
+if __name__ == "__main__":
+    demo.launch(server_name="0.0.0.0", share=False)