Alessio Grancini commited on
Commit
563e8cc
·
verified ·
1 Parent(s): afdb8e3

Update app.py

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Files changed (1) hide show
  1. app.py +8 -1
app.py CHANGED
@@ -230,6 +230,7 @@ def get_bbox_from_mask(mask):
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  @spaces.GPU
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  def get_detection_data(image_data):
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  try:
 
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  if isinstance(image_data, dict):
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  nested_dict = image_data.get("image", {}).get("image", {})
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  full_data_url = nested_dict.get("data", "")
@@ -249,10 +250,13 @@ def get_detection_data(image_data):
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  img = np.array(img)
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  img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
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  image = utils.resize(img)
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  image_segmentation, objects_data = img_seg.predict(image)
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  depthmap, depth_colormap = depth_estimator.make_prediction(image)
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  detections = []
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  for obj in objects_data:
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  cls_id, cls_name, center, mask, _ = obj
@@ -269,6 +273,8 @@ def get_detection_data(image_data):
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  "distance": depth_value
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  })
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  response = {
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  "detections": detections,
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  "segmentation_url": save_image_to_url(image_segmentation),
@@ -276,7 +282,7 @@ def get_detection_data(image_data):
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  "distance_url": save_image_to_url(utils.draw_depth_info(image, depthmap, objects_data)),
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  "point_cloud_url": save_plot_to_url(utils.generate_obj_pcd(depthmap, objects_data)),
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  "camera_matrix": get_camera_matrix(depth_estimator),
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- "camera_position": [0, 0, 0] # Assumed at origin based on camera intrinsics
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  }
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  return response
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@@ -285,6 +291,7 @@ def get_detection_data(image_data):
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  return {"error": str(e)}
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  def cancel():
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  CANCEL_PROCESSING = True
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  @spaces.GPU
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  def get_detection_data(image_data):
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  try:
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+ # Decode base64 image
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  if isinstance(image_data, dict):
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  nested_dict = image_data.get("image", {}).get("image", {})
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  full_data_url = nested_dict.get("data", "")
 
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  img = np.array(img)
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  img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
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+ # Run detection
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  image = utils.resize(img)
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  image_segmentation, objects_data = img_seg.predict(image)
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  depthmap, depth_colormap = depth_estimator.make_prediction(image)
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+ print("✅ Detected Objects:", objects_data) # Log detected objects
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+
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  detections = []
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  for obj in objects_data:
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  cls_id, cls_name, center, mask, _ = obj
 
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  "distance": depth_value
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  })
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+ print("✅ Processed Detections:", detections) # Log final detections
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+
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  response = {
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  "detections": detections,
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  "segmentation_url": save_image_to_url(image_segmentation),
 
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  "distance_url": save_image_to_url(utils.draw_depth_info(image, depthmap, objects_data)),
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  "point_cloud_url": save_plot_to_url(utils.generate_obj_pcd(depthmap, objects_data)),
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  "camera_matrix": get_camera_matrix(depth_estimator),
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+ "camera_position": [0, 0, 0]
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  }
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  return response
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  return {"error": str(e)}
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+
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  def cancel():
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  CANCEL_PROCESSING = True
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