testing outputs

app.py

@@ -13,6 +13,8 @@ import matplotlib.pyplot as plt
 from transformers import AutoModelForMaskGeneration, AutoProcessor, pipeline
 import gradio as gr
 import spaces
+from plotly import graph_objects as go
+import plotly.express as px
 
 @dataclass
 class BoundingBox:
@@ -178,15 +180,13 @@ def draw_classification_boxes(image_with_insects, detections):
             f"{label}: {score:.2f}",
             (box.xmin, box.ymin - baseline),
             cv2.FONT_HERSHEY_SIMPLEX,
-             0.5,
+            0.5,
             (255, 255, 255),
              2
         )
     return image_with_insects
 
 def plot_detections_plotly(image: np.ndarray, detections: List[DetectionResult]) -> str:
-    from plotly import graph_objects as go
-    import plotly.express as px
     fig = px.imshow(image)
     class_colors = {i: f'rgb({random.randint(0, 255)}, {random.randint(0, 255)}, {random.randint(0, 255)})' for i in range(len(detections))}
     for idx, detection in enumerate(detections):
@@ -225,7 +225,9 @@ def process_image(image):
     yellow_background_with_insects = create_yellow_background_with_insects(np.array(original_image), detections)
     yellow_background_with_boxes = draw_classification_boxes(yellow_background_with_insects.copy(), detections)
     plotly_image_path = plot_detections_plotly(original_image, detections)
-    return annotated_image, yellow_background_with_boxes, plotly_image_path
+    with open(plotly_image_path, 'r') as file:
+        plotly_html = file.read()
+    return annotated_image, yellow_background_with_boxes, plotly_html
 
 gr.Interface(
     fn=process_image,