Create app.py

app.py

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+import gradio as gr
+import spaces
+from cellpose import models
+import numpy as np
+import cv2
+import matplotlib.pyplot as plt
+import tempfile
+from PIL import Image
+import io
+from huggingface_hub import hf_hub_download
+
+HF_REPO_ID = "myang4218/cellposemodel"
+MODEL_OPTIONS = {
+    "Hemocytometer Model": "hemocytometermodel.npy",
+    "General Model": "generalmodel.npy"
+}
+loaded_models = {}
+
+# Global variable for region coordinates (can remain global if only for info display)
+current_region_coords = None
+
+def debug_editor_data(editor_data):
+    """Debug function to understand the structure of ImageEditor data"""
+    if editor_data is None:
+        return "No data provided"
+    info = f"Type: {type(editor_data)}\n"
+    if isinstance(editor_data, dict):
+        info += f"Keys: {list(editor_data.keys())}\n"
+        for key, value in editor_data.items():
+            info += f"  {key}: {type(value)}\n"
+            if key == 'layers' and value:
+                info += f"    Layers count: {len(value)}\n"
+                for i, layer in enumerate(value):
+                    info += f"    Layer {i}: {type(layer)}\n"
+                    if hasattr(layer, 'size'):
+                        info += f"      Size: {layer.size}\n"
+                        info += f"      Mode: {layer.mode}\n"
+    else: # Direct PIL Image
+        if hasattr(editor_data, 'size'):
+            info += f"Size: {editor_data.size}\n"
+            info += f"Mode: {editor_data.mode}\n"
+    return info
+
+def extract_region_from_editor(editor_data):
+    """Extract the selected region from ImageEditor data"""
+    if editor_data is None:
+        print("DEBUG: extract_region_from_editor - editor_data is None")
+        return None, None
+    
+    print(f"DEBUG: extract_region_from_editor - editor_data type: {type(editor_data)}")
+    
+    if isinstance(editor_data, dict):
+        background = editor_data.get('background')
+        layers = editor_data.get('layers', [])
+        
+        if background is None:
+            print("DEBUG: extract_region_from_editor - background is None")
+            return None, None
+        
+        background_np = np.array(background)
+        print(f"DEBUG: extract_region_from_editor - background_np shape: {background_np.shape}")
+        
+        if layers and len(layers) > 0:
+            selection_layer = layers[0]
+            selection_np = np.array(selection_layer)
+            print(f"DEBUG: extract_region_from_editor - selection_np shape: {selection_np.shape}")
+            
+            if len(selection_np.shape) == 3:
+                if selection_np.shape[2] == 4:  # RGBA
+                    mask = selection_np[:, :, 3] > 0
+                else:  # RGB
+                    mask = np.any(selection_np > 0, axis=2)
+            else:
+                mask = selection_np > 0
+            
+            coords = np.where(mask)
+            if len(coords[0]) > 0:
+                y_min, y_max = coords[0].min(), coords[0].max()
+                x_min, x_max = coords[1].min(), coords[1].max()
+                
+                pad = 5
+                h, w = background_np.shape[:2]
+                y_min = max(0, y_min - pad)