Duplicate from IrishMehta/fraud-detection-idnet-three-class

Co-authored-by: Irish Mehta <IrishMehta@users.noreply.huggingface.co>

.gitattributes

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+*.arrow filter=lfs diff=lfs merge=lfs -text
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.ipynb_checkpoints/README-checkpoint.md

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+---
+license: mit
+library_name: transformers
+pipeline_tag: image-classification
+tags:
+  - image-classification
+  - computer-vision
+---
+
+# Fraud Detection Image Classification Model
+
+This model classifies images into 3 classes:
+- Class 0: Non fraudulent images, passed the safety check
+- Class 1: Fraudulent images of type 5- Inpaint and Rewriting found in the ID
+- Class 2: Fraudulent images of type 6- Cropping and replacement found in the ID
+
+## Usage
+
+from transformers import pipeline
+
+classifier = pipeline("image-classification", model="IrishMehta/fraud-detection-idnet-three-class")
+result = classifier("path/to/image.jpg")
+print(result)
+

.ipynb_checkpoints/config-checkpoint.json

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+{
+  "hidden_size": 2048,
+  "id2label": {
+    "0": "0",
+    "1": "1",
+    "2": "2"
+  },
+  "label2id": {
+    "0": 0,
+    "1": 1,
+    "2": 2
+  },
+  "transformers_version": "4.45.2"
+}

.ipynb_checkpoints/preprocessor_config-checkpoint.json

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+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextFeatureExtractor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}

README.md

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+---
+language: en
+license: mit
+tags:
+- image-classification
+- computer-vision
+- fraud-detection
+pipeline_tag: image-classification
+---
+
+# Fraud Detection Image Classification Model
+
+This model classifies images into 3 classes:
+- Class 0: Non fraudulent images, passed the safety check
+- Class 1: Fraudulent images of type 5- Inpaint and Rewriting found in the ID
+- Class 2: Fraudulent images of type 6- Cropping and replacement found in the ID
+
+## Usage
+
+from transformers import pipeline
+
+classifier = pipeline("image-classification", model="IrishMehta/fraud-detection-idnet-three-class")
+result = classifier("path/to/image.jpg")
+print(result)
+

config.json

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+{"architectures": ["ResNetForImageClassification"], "model_type": "resnet", "num_labels": 3, "id2label": {"0": "0", "1": "1", "2": "2"}, "label2id": {"0": 0, "1": 1, "2": 2}, "hidden_size": 2048, "problem_type": "single_label_classification", "pipeline_tag": "image-classification", "AutoModelForImageClassification": "transformers.models.resnet.modeling_resnet.ResNetForImageClassification"}

preprocessor_config.json

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+{
+  "crop_pct": 0.875,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.485,
+    0.456,
+    0.406
+  ],
+  "image_processor_type": "ConvNextFeatureExtractor",
+  "image_std": [
+    0.229,
+    0.224,
+    0.225
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  }
+}

pytorch_model.bin

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+size 94371786