commit files to HF hub

README.md

@@ -1,56 +1,56 @@
 ---
-    tags:
-    - image-classification
-    - pytorch
-    - huggingpics
+tags:
+- image-classification
+- pytorch
+- huggingpics
+metrics:
+- accuracy
+
+model-index:
+- name: krenzcolor_chkpt_classifier
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
     metrics:
-    - accuracy
+      - name: Accuracy
+        type: accuracy
+        value: 0.3660714328289032
+---
+
+# krenzcolor_chkpt_classifier
+
+
+Autogenerated by HuggingPics🤗🖼️
+
+Create your own image classifier for **anything** by running [the demo on Google Colab](https://colab.research.google.com/github/nateraw/huggingpics/blob/main/HuggingPics.ipynb).
+
+Report any issues with the demo at the [github repo](https://github.com/nateraw/huggingpics).
+
+
+## Example Images
 
-    model-index:
-    - name: krenzcolor_chkpt_classifier
-    results:
-    - task:
-        name: Image Classification
-        type: image-classification
-        metrics:
-        - name: Accuracy
-            type: accuracy
-            value: 0.4107142984867096
-    ---
 
-    # krenzcolor_chkpt_classifier
+#### chk1_fail
 
-    
-    Autogenerated by HuggingPics🤗🖼️
+![chk1_fail](images/chk1_fail.jpg)
 
-    Create your own image classifier for **anything** by running [the demo on Google Colab](https://colab.research.google.com/github/nateraw/huggingpics/blob/main/HuggingPics.ipynb).
+#### chk1_pass
 
-    Report any issues with the demo at the [github repo](https://github.com/nateraw/huggingpics).
-    
+![chk1_pass](images/chk1_pass.jpg)
 
-    ## Example Images
+#### chk2_fail
 
-    
-    #### chk1_fail
+![chk2_fail](images/chk2_fail.jpg)
 
-    ![chk1_fail](images/chk1_fail.jpg)
-    
-    #### chk1_pass
+#### chk2_pass
 
-    ![chk1_pass](images/chk1_pass.jpg)
-    
-    #### chk2_fail
+![chk2_pass](images/chk2_pass.jpg)
 
-    ![chk2_fail](images/chk2_fail.jpg)
-    
-    #### chk2_pass
+#### chk3_fail
 
-    ![chk2_pass](images/chk2_pass.jpg)
-    
-    #### chk3_fail
+![chk3_fail](images/chk3_fail.jpg)
 
-    ![chk3_fail](images/chk3_fail.jpg)
-    
-    #### chk3_pass
+#### chk3_pass
 
-    ![chk3_pass](images/chk3_pass.jpg)
+![chk3_pass](images/chk3_pass.jpg)

pipeline.py

@@ -0,0 +1,29 @@
+from torchvision import transforms
+from transformers import ImageClassificationPipeline
+import torch
+
+
+class PairClassificationPipeline(ImageClassificationPipeline):
+    pipe_to_tensor = transforms.ToTensor()
+    pipe_to_pil = transforms.ToPILImage()
+
+    def preprocess(self, image):       
+        left_image, right_image = self.horizontal_split_image(image)
+        model_inputs = self.extract_split_feature(left_image, right_image)
+        # model_inputs = super().preprocess(image)
+        # print(model_inputs['pixel_values'].shape)
+        return model_inputs
+
+    def horizontal_split_image(self, image):
+        # image = image.resize((448,224))
+        w, h = image.size
+        half_w = w//2
+        left_image = image.crop([0,0,half_w,h])
+        right_image = image.crop([half_w,0,2*half_w,h])
+        return left_image, right_image
+    
+    def extract_split_feature(self, left_image, right_image):
+        model_inputs = self.feature_extractor(images=left_image, return_tensors=self.framework)
+        right_inputs = self.feature_extractor(images=right_image, return_tensors=self.framework)
+        model_inputs['pixel_values'] = torch.cat([model_inputs['pixel_values'],right_inputs['pixel_values']], dim=1)
+        return model_inputs

pytorch_model.bin

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runs/events.out.tfevents.1666948795.sa103.19420.0

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