Making progress on adding a map

app.py

@@ -9,7 +9,7 @@ import cv2 as cv
 import numpy as np
 
 from transformers import DetrImageProcessor, DetrForSegmentation, MaskFormerImageProcessor, MaskFormerForInstanceSegmentation
-from transformers.models.detr.feature_extraction_detr import rgb_to_id
+from transformers.image_transforms import id_to_rgb
 
 
 
@@ -95,9 +95,17 @@ def segment_images(model_name,url_input,image_input,threshold):
         for r in results["segments_info"]:
             contour_list, hierarchy = contour_map(results["segmentation"], r["id"])
             label_name = model.config.id2label[r["label_id"]]
-            return_string += f"ID: {r['id']}, Contour Length: {len(contour_list)}, Label Name: {label_name}, Score: {r['score']}\n"
+            return_string += f"ID: {r['id']}\t Contour Count: {len(contour_list)}\t Score: {r['score']}\t Label Name: {label_name},\n"
 
-        return image, return_string
+        r_shape = results["segmentation"].shape
+        new_image = np.zeros((r[0], r[1], 3), dtype=np.uint8)
+        new_image[:, :, 0] = results["segmentation"].numpy()[:, :]
+        new_image[:, :, 1] = (new_image[:, :, 0] * 2) %256
+        new_image[:, :, 2] = (new_image[:, :, 0] * 3) %256
+
+        new_image = Image.fromarray(new_image)
+
+        return new_image, return_string
         
         pass
     else:
@@ -115,8 +123,8 @@ title = """<h1 id="title">Image Segmentation with Various Models</h1>"""
 description = """
 Links to HuggingFace Models:
 
-- [facebook/detr-resnet-50-panoptic](https://huggingface.co/facebook/detr-resnet-50-panoptic)  
-- [facebook/detr-resnet-101-panoptic](https://huggingface.co/facebook/detr-resnet-101-panoptic)
+- [facebook/detr-resnet-50-panoptic](https://huggingface.co/facebook/detr-resnet-50-panoptic)   (Not implemented YET)
+- [facebook/detr-resnet-101-panoptic](https://huggingface.co/facebook/detr-resnet-101-panoptic) (Not implemented YET)
 - [facebook/maskformer-swin-large-coco](https://huggingface.co/facebook/maskformer-swin-large-coco)
 """
 

interpretter_notes.py

@@ -154,4 +154,22 @@ def quick_function(id_number):
 ...     print(f'{model.config.id2label[results["segments_info"][id_number-1]["label_id"]]}, {results["segments_info"][id_number -1]["score"]}, Contour Count: {len(c)}')
 ...     show_mask_for_number_over_image(results["segmentation"],id_number, TEST_IMAGE)
 ... 
+"""
+
+"""
+>>> m = results["segmentation"].cpu().numpy()
+>>> new_dim = (m[0], m[1], 3)
+>>> new_dim
+(array([43, 43, 43, ..., 21, 21, 21], dtype=int32), array([43, 43, 43, ..., 21, 21, 21], dtype=int32), 3)
+>>> new_dim = (m.shape[0], m.shape[1], 3)
+>>> all_z = np.zeros(new_dim, dtype=np.uint8)
+
+>>> z = np.zeros((m.shape[0], m.shape[1], 3), dtype=np.uint8)
+>>> z[:, :, 0] = m[:, :]
+>>> z[0,0]
+array([43,  0,  0], dtype=uint8)
+>>> z[0, 0]
+array([43,  0,  0], dtype=uint8)
+>>> m[0, 0]
+43
 """

understand.py

@@ -8,7 +8,7 @@ import cv2 as cv
 
 from transformers import DetrImageProcessor, DetrForSegmentation, MaskFormerImageProcessor, MaskFormerForInstanceSegmentation
 # from transformers.models.detr.feature_extraction_detr import rgb_to_id
-from transformers.image_transforms import rgb_to_id
+from transformers.image_transforms import rgb_to_id, id_to_rgb
 
 TEST_IMAGE = Image.open(r"images/9999999_00783_d_0000358.jpg")
 MODEL_NAME_DETR = "facebook/detr-resnet-50-panoptic"